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Controlled Experiments: Definition, Steps, Results, Uses

Controlled experiments ensure valid and reliable results by minimizing biases and controlling variables effectively.

Rigorous planning, ethical considerations, and precise data analysis are vital for successful experiment execution and meaningful conclusions.

Real-world applications demonstrate the practical impact of controlled experiments, guiding informed decision-making in diverse domains.

Controlled experiments are the systematic research method where variables are intentionally manipulated and controlled to observe the effects of a particular phenomenon. It aims to isolate and measure the impact of specific variables, ensuring a more accurate causality assessment.

Table of Contents

Interesting Science Videos

Importance of controlled experiments in various fields

Controlled experiments are significant across diverse fields, including science, psychology, economics, healthcare, and technology.

They provide a systematic approach to test hypotheses, establish cause-and-effect relationships, and validate the effectiveness of interventions or solutions.

Why Controlled Experiments Matter? 

Validity and reliability of results.

Controlled experiments uphold the gold standard for scientific validity and reliability. By meticulously controlling variables and conditions, researchers can attribute observed outcomes accurately to the independent variable being tested. This precision ensures that the findings can be replicated and are trustworthy.

Minimizing Biases and Confounding Variables

One of the core benefits of controlled experiments lies in their ability to minimize biases and confounding variables. Extraneous factors that could distort results are mitigated through careful control and randomization. This enables researchers to isolate the effects of the independent variable, leading to a more accurate understanding of causality.

Achieving Causal Inference

Controlled experiments provide a strong foundation for establishing causal relationships between variables. Researchers can confidently infer causation by manipulating specific variables and observing resulting changes. The capability informs decision-making, policy formulation, and advancements across various fields.

Planning a Controlled Experiment

Formulating research questions and hypotheses.

Formulating clear research questions and hypotheses is paramount at the outset of a controlled experiment. These inquiries guide the direction of the study, defining the variables of interest and setting the stage for structured experimentation.

Well-defined questions and hypotheses contribute to focused research and facilitate meaningful data collection.

Identifying Variables and Control Groups

Identifying and defining independent, dependent, and control variables is fundamental to experimental planning. 

Precise identification ensures that the experiment is designed to isolate the effect of the independent variable while controlling for other influential factors. Establishing control groups allows for meaningful comparisons and robust analysis of the experimental outcomes.

Designing Experimental Procedures and Protocols

Careful design of experimental procedures and protocols is essential for a successful controlled experiment. The step involves outlining the methodology, data collection techniques, and the sequence of activities in the experiment. 

A well-designed experiment is structured to maintain consistency, control, and accuracy throughout the study, thereby enhancing the validity and credibility of the results.

Conducting a Controlled Experiment

Randomization and participant selection.

Randomization is a critical step in ensuring the fairness and validity of a controlled experiment. It involves assigning participants to different experimental conditions in a random and unbiased manner. 

The selection of participants should accurately represent the target population, enhancing the results’ generalizability.

Data Collection Methods and Instruments

Selecting appropriate data collection methods and instruments is pivotal in gathering accurate and relevant data. Researchers often employ surveys, observations, interviews, or specialized tools to record and measure the variables of interest. 

The chosen methods should align with the experiment’s objectives and provide reliable data for analysis.

Monitoring and Maintaining Experimental Conditions

Maintaining consistent and controlled experimental conditions throughout the study is essential. Regular monitoring helps ensure that variables remain constant and uncontaminated, reducing the risk of confounding factors. 

Rigorous monitoring protocols and timely adjustments are crucial for the accuracy and reliability of the experiment.

Analysing Results and Drawing Conclusions

Data analysis techniques.

Data analysis involves employing appropriate statistical and analytical techniques to process the collected data. This step helps derive meaningful insights, identify patterns, and draw valid conclusions. 

Common techniques include regression analysis, t-tests , ANOVA , and more, tailored to the research design and data type .

Interpretation of Results

Interpreting the results entails understanding the statistical outcomes and their implications for the research objectives. 

Researchers analyze patterns, trends, and relationships revealed by the data analysis to infer the experiment’s impact on the variables under study. Clear and accurate interpretation is crucial for deriving actionable insights.

Implications and Potential Applications

Identifying the broader implications and potential applications of the experiment’s results is fundamental. Researchers consider how the findings can inform decision-making, policy development, or further research. 

Understanding the practical implications helps bridge the gap between theoretical insights and real-world application.

Common Challenges and Solutions

Addressing ethical considerations.

Ethical challenges in controlled experiments include ensuring informed consent, protecting participants’ privacy, and minimizing harm. 

Solutions involve thorough ethics reviews, transparent communication with participants, and implementing safeguards to uphold ethical standards throughout the experiment.

Dealing with Sample Size and Statistical Power

The sample size is crucial for achieving statistically significant results. Adequate sample sizes enhance the experiment’s power to detect meaningful effects accurately. 

Statistical power analysis guides researchers in determining the optimal sample size for the experiment, minimizing the risk of type I and II errors .

Mitigating Unforeseen Variables

Unforeseen variables can introduce bias and affect the experiment’s validity. Researchers employ meticulous planning and robust control measures to minimize the impact of unforeseen variables. 

Pre-testing and pilot studies help identify potential confounders, allowing researchers to adapt the experiment accordingly.

A controlled experiment involves meticulous planning, precise execution, and insightful analysis. Adhering to ethical standards, optimizing sample size, and adapting to unforeseen variables are key challenges that require thoughtful solutions. 

Real-world applications showcase the transformative potential of controlled experiments across varied domains, emphasizing their indispensable role in evidence-based decision-making and progress.

• https://www.khanacademy.org/science/biology/intro-to-biology/science-of-biology/a/experiments-and-observations
• https://www.scribbr.com/methodology/controlled-experiment/
• https://link.springer.com/10.1007/978-1-4899-7687-1_891
• http://ai.stanford.edu/~ronnyk/GuideControlledExperiments.pdf
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6776925/
• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4017459/
• https://www.merriam-webster.com/dictionary/controlled%20experiment

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Controlled Experiment

Reviewed by: BD Editors

Controlled Experiment Definition

A controlled experiment is a scientific test that is directly manipulated by a scientist, in order to test a single variable at a time. The variable being tested is the independent variable , and is adjusted to see the effects on the system being studied. The controlled variables are held constant to minimize or stabilize their effects on the subject. In biology, a controlled experiment often includes restricting the environment of the organism being studied. This is necessary to minimize the random effects of the environment and the many variables that exist in the wild.

In a controlled experiment, the study population is often divided into two groups. One group receives a change in a certain variable, while the other group receives a standard environment and conditions. This group is referred to as the control group , and allows for comparison with the other group, known as the experimental group . Many types of controls exist in various experiments, which are designed to ensure that the experiment worked, and to have a basis for comparison. In science, results are only accepted if it can be shown that they are statistically significant . Statisticians can use the difference between the control group and experimental group and the expected difference to determine if the experiment supports the hypothesis , or if the data was simply created by chance.

Examples of Controlled Experiment

Music preference in dogs.

Do dogs have a taste in music? You might have considered this, and science has too. Believe it or not, researchers have actually tested dog’s reactions to various music genres. To set up a controlled experiment like this, scientists had to consider the many variables that affect each dog during testing. The environment the dog is in when listening to music, the volume of the music, the presence of humans, and even the temperature were all variables that the researches had to consider.

In this case, the genre of the music was the independent variable. In other words, to see if dog’s change their behavior in response to different kinds of music, a controlled experiment had to limit the interaction of the other variables on the dogs. Usually, an experiment like this is carried out in the same location, with the same lighting, furniture, and conditions every time. This ensures that the dogs are not changing their behavior in response to the room. To make sure the dogs don’t react to humans or simply the noise of the music, no one else can be in the room and the music must be played at the same volume for each genre. Scientist will develop protocols for their experiment, which will ensure that many other variables are controlled.

This experiment could also split the dogs into two groups, only testing music on one group. The control group would be used to set a baseline behavior, and see how dogs behaved without music. The other group could then be observed and the differences in the group’s behavior could be analyzed. By rating behaviors on a quantitative scale, statistics can be used to analyze the difference in behavior, and see if it was large enough to be considered significant. This basic experiment was carried out on a large number of dogs, analyzing their behavior with a variety of different music genres. It was found that dogs do show more relaxed and calm behaviors when a specific type of music plays. Come to find out, dogs enjoy reggae the most.

Scurvy in Sailors

In the early 1700s, the world was a rapidly expanding place. Ships were being built and sent all over the world, carrying thousands and thousands of sailors. These sailors were mostly fed the cheapest diets possible, not only because it decreased the costs of goods, but also because fresh food is very hard to keep at sea. Today, we understand that lack of essential vitamins and nutrients can lead to severe deficiencies that manifest as disease. One of these diseases is scurvy.

Scurvy is caused by a simple vitamin C deficiency, but the effects can be brutal. Although early symptoms just include general feeling of weakness, the continued lack of vitamin C will lead to a breakdown of the blood cells and vessels that carry the blood. This results in blood leaking from the vessels. Eventually, people bleed to death internally and die. Before controlled experiments were commonplace, a simple physician decided to tackle the problem of scurvy. James Lind, of the Royal Navy, came up with a simple controlled experiment to find the best cure for scurvy.

He separated sailors with scurvy into various groups. He subjected them to the same controlled condition and gave them the same diet, except one item. Each group was subjected to a different treatment or remedy, taken with their food. Some of these remedies included barley water, cider and a regiment of oranges and lemons. This created the first clinical trial , or test of the effectiveness of certain treatments in a controlled experiment. Lind found that the oranges and lemons helped the sailors recover fast, and within a few years the Royal Navy had developed protocols for growing small leafy greens that contained high amounts of vitamin C to feed their sailors.

Related Biology Terms

• Field Experiment – An experiment conducted in nature, outside the bounds of total control.
• Independent Variable – The thing in an experiment being changed or manipulated by the experimenter to see effects on the subject.
• Controlled Variable – A thing that is normalized or standardized across an experiment, to remove it from having an effect on the subject being studied.
• Control Group – A group of subjects in an experiment that receive no independent variable, or a normalized amount, to provide comparison.

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Controlled Experiments | Methods & Examples of Control

Published on 19 April 2022 by Pritha Bhandari . Revised on 10 October 2022.

In experiments , researchers manipulate independent variables to test their effects on dependent variables. In a controlled experiment , all variables other than the independent variable are controlled or held constant so they don’t influence the dependent variable.

Controlling variables can involve:

• Holding variables at a constant or restricted level (e.g., keeping room temperature fixed)
• Measuring variables to statistically control for them in your analyses
• Balancing variables across your experiment through randomisation (e.g., using a random order of tasks)

Table of contents

Why does control matter in experiments, methods of control, problems with controlled experiments, frequently asked questions about controlled experiments.

Control in experiments is critical for internal validity , which allows you to establish a cause-and-effect relationship between variables.

• Your independent variable is the colour used in advertising.
• Your dependent variable is the price that participants are willing to pay for a standard fast food meal.

Extraneous variables are factors that you’re not interested in studying, but that can still influence the dependent variable. For strong internal validity, you need to remove their effects from your experiment.

• Design and description of the meal
• Study environment (e.g., temperature or lighting)
• Participant’s frequency of buying fast food
• Participant’s familiarity with the specific fast food brand
• Participant’s socioeconomic status

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You can control some variables by standardising your data collection procedures. All participants should be tested in the same environment with identical materials. Only the independent variable (e.g., advert colour) should be systematically changed between groups.

Other extraneous variables can be controlled through your sampling procedures . Ideally, you’ll select a sample that’s representative of your target population by using relevant inclusion and exclusion criteria (e.g., including participants from a specific income bracket, and not including participants with colour blindness).

By measuring extraneous participant variables (e.g., age or gender) that may affect your experimental results, you can also include them in later analyses.

After gathering your participants, you’ll need to place them into groups to test different independent variable treatments. The types of groups and method of assigning participants to groups will help you implement control in your experiment.

Control groups

Controlled experiments require control groups . Control groups allow you to test a comparable treatment, no treatment, or a fake treatment, and compare the outcome with your experimental treatment.

You can assess whether it’s your treatment specifically that caused the outcomes, or whether time or any other treatment might have resulted in the same effects.

• A control group that’s presented with red advertisements for a fast food meal
• An experimental group that’s presented with green advertisements for the same fast food meal

Random assignment

To avoid systematic differences between the participants in your control and treatment groups, you should use random assignment .

This helps ensure that any extraneous participant variables are evenly distributed, allowing for a valid comparison between groups .

Random assignment is a hallmark of a ‘true experiment’ – it differentiates true experiments from quasi-experiments .

Masking (blinding)

Masking in experiments means hiding condition assignment from participants or researchers – or, in a double-blind study , from both. It’s often used in clinical studies that test new treatments or drugs.

Sometimes, researchers may unintentionally encourage participants to behave in ways that support their hypotheses. In other cases, cues in the study environment may signal the goal of the experiment to participants and influence their responses.

Using masking means that participants don’t know whether they’re in the control group or the experimental group. This helps you control biases from participants or researchers that could influence your study results.

Although controlled experiments are the strongest way to test causal relationships, they also involve some challenges.

Difficult to control all variables

Especially in research with human participants, it’s impossible to hold all extraneous variables constant, because every individual has different experiences that may influence their perception, attitudes, or behaviors.

But measuring or restricting extraneous variables allows you to limit their influence or statistically control for them in your study.

Risk of low external validity

Controlled experiments have disadvantages when it comes to external validity – the extent to which your results can be generalised to broad populations and settings.

The more controlled your experiment is, the less it resembles real world contexts. That makes it harder to apply your findings outside of a controlled setting.

There’s always a tradeoff between internal and external validity . It’s important to consider your research aims when deciding whether to prioritise control or generalisability in your experiment.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

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Understanding Controlled Experiments

1. introduction: the scientific method.

The scientific method is typically taught as a step-by-step sequence. Drag the steps below, listed in alphabetical order, into an order that matches the steps described in the table.

[qwiz style=”width: 700px !important; min-height: 400px !important;”]

[h] Steps of the Scientific Method

[l] Drawing conclusions

[f*] Correct!

[fx] No. Please try again.

[l] Formulating hypotheses

[l] Making observations

[f*] Excellent!

[fx] No, that’s not correct. Please try again.

[l] Performing experiments

[f*] Great!

2. Interactive Reading: A Case Study: The link between cancer and smoking. Initial observations

To learn about the scientific method and experimentation, we’ll look at a very simplified history of the discovery of the link between smoking tobacco and cancer. 1

1 For a detailed view of this story, follow the links to tobaccocontrol.bmj.com at the end of this tutorial. Much of the information below comes from that site.

[qwiz qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments 1: Cancer and Smoking 1″]

[h]Interactive Reading: The Link between Cancer and Smoking

[i]Carefully read what follows, dragging in the words on top to the right place.

[q labels = “top”]

It hasn’t always been known that smoking tobacco caused lung cancer. In the 1500s, tobacco was praised for its supposed health benefits. Lung cancer itself was once extremely _______ . But mechanical production of cigarettes, free distribution of cigarettes to soldiers, and mass marketing caused a global lung cancer ____________ that began in the 1900s and continues today.

The first observations of the connection started around 1900. The key observation was the rise in _______ cancer rates. Among the first to notice this connection was a German medical student, Hermann Rottman, who noticed higher rates of lung cancer among German __________ workers. Rottman suspected that exposure to tobacco dust was causing cancer.

[l] epidemic

[l] tobacco

By the 1920s, the increasing rate of lung cancer began to be linked with _________ , but other possible causes for increased lung cancer rates were also considered. These included exposure to poison gas suffered by soldiers during World War One and exposure to the tar that was increasingly used on roads as driving became more common.

In the 1930s, population studies in German hospitals led to the discovery that lung cancer patients were far ___________ to have smoked than patients who didn’t have cancer. By the 1950s, American doctors were able to calculate that “smokers of 35 cigarettes per day increased their odds of ________ from lung cancer by a factor of 40.” (tobaccocontrol.bmj.com).

So, by that point there was a clear __________ : if someone smokes, then they have a higher chance of developing lung cancer.  Now let’s look at how experiments could be designed to confirm that hypothesis.

[l] hypothesis

[l] more likely

[l] smoking

3. Controlled Experiments: General Features

For the sake of simplicity (and learning), the experiment described below is somewhat different from the actual animal experiments that were performed to help establish the link between tobacco smoke and cancer.

Let’s start by reviewing what an experiment is: it’s a controlled form of observation that lets you observe one thing at a time.  As you read what follows, refer to the diagram below.

[qwiz style = “width: 528px; min-height:0px; border: 3px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: General Features”]

[h]Quiz: Controlled Experiments, General Features

[q] Experiments try to test the effect of ONE thing at a time. The thing that you test is called the independent variable. 

In relationship to our hypothesis ( if someone smokes, they have a higher chance of developing lung cancer) , what’s the independent variable?

[c]wqBsdW5nIGNhbmNlcg==[Qq]

[c]IHRvYmFjY2 8gc21va2U=[Qq]

[f]Tm8uIEx1bmcgY2FuY2VyIGlzIHdoYXQgaGFwcGVucyBpbiByZXNwb25zZQ==[Qq]

[f]WWVzLiBJbiByZWxhdGlvbnNoaXAgdG8gb3VyIGh5cG90aGVzaXMsIHRoZSBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcw== IHRvYmFjY28gc21va2U= LiBJdCYjODIxNztzIHRoZSB0aGluZyB0aGF0IHdlJiM4MjE3O3JlIGdvaW5nIHRvIHRlc3Qu[Qq]

[q]Because we’re testing a harmful substance, we’re not going to test humans, but animals related to humans (like mice or rats). Keep that in mind when we talk about “groups” and “individuals” below.

• the standard for comparison.
• not exposed to the independent variable.
• The second group is the  experimental group . This group gets exposed to the independent variable.

In relationship to our hypothesis about smoking and cancer, what will be our control group?

[c]VGhlIHJhdHMgdGhhdCBhcmUgZXhwb3NlZCB0byB0b2JhY2NvIHNtb2tlLg==[Qq]

[c]VGhlIHJhdHMg dGhhdCBhcmUg bm90 IGV4cG9zZWQgdG8gdG9iYWNjbyBzbW9rZQ==[Qq]

[c]QW55IHJhdHMgdGhhdCBkZXZlbG9wIGNhbmNlciB3aWxsIG1ha2UgdXAgdGhlIGNvbnRyb2wgZ3JvdXAu[Qq]

[f]Tm8uIElmIG91ciBpbmRlcGVuZGVudCB2YXJpYWJsZSBpcyB0b2JhY2NvIHNtb2tlLMKgdGhlbiB0aGUgcmF0cyBleHBvc2VkIHRvIHRvYmFjY28gc21va2UgYXJlIHRoZSBleHBlcmltZW50YWwgZ3JvdXAu[Qq]

[f]RXhjZWxsZW50LiBJZiBvdXIgaW5kZXBlbmRlbnQgdmFyaWFibGUgaXMgdG9iYWNjbyBzbW9rZSzCoHRoZW4gdGhlIHJhdHMgdGhhdCBhcmUgTk9UIGV4cG9zZWQgdG8gdG9iYWNjbyBzbW9rZSBhcmUgdGhlIGNvbnRyb2zCoGdyb3VwICh0aGV5JiM4MjE3O3JlIA== bm90 IGV4cG9zZWQgdG8gdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlKQ==[Qq]

[f]Tm8uIFRoaXMgcXVlc3Rpb24gaXMgYWJvdXQgdGhlIGdyb3VwcyB5b3Ugc2V0IHVwIHRvIHRlc3QgdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlLiBEZXZlbG9wbWVudCBvZiBjYW5jZXIgaXMgYSBwb3NzaWJsZSBlZmZlY3Qgb2YgdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlLCBidXQgaXQmIzgyMTc7cyBub3QgY29ubmVjdGVkIHdpdGggdGhlIGRlc2lnbiBvZiB5b3VyIGV4cGVyaW1lbnQu[Qq]

[q] What’s the experimental group?

[c]VGhlIHJhdHMgdGhhdCBhcmUgZXhwb3 NlZCB0byB0b2JhY2NvIHNtb2tlLg==[Qq]

[c]VGhlIHJhdHMgdGhhdCBhcmUg bm90 IGV4cG9zZWQgdG8gdG9iYWNjbyBzbW9rZQ==[Qq]

[f]Q29ycmVjdC4gVGhhdCByYXRzIHRoYXQgYXJlIGV4cG9zZWQgdG8gdG9iYWNjbyBzbW9rZSB3aWxsIG1ha2UgdXAgdGhlIGV4cGVyaW1lbnRhbCBncm91cC4=[Qq]

[f]Tm8uIFRoZSByYXRzIHRoYXQgYXJlIG5vdCBleHBvc2VkIHRvIHRvYmFjY28gc21va2UgbWFrZSB1cCB0aGUgY29udHJvbCBncm91cC4=[Qq]

[q]An experiment is going to have some observable outcome. That outcome is called the dependent variable.  In relationship to our hypothesis ( if someone smokes, they have a higher chance of developing lung cancer) , what’s the dependent variable?

[c]dG9iYWNjbyBzbW9rZQ==[Qq]

[c]dG hl IHJhdGUgb2YgbHVuZyBjYW5jZXI= [Qq]

[f]Tm8uIFRvYmFjY28gc21va2UgaXMgdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlICh0aGUgdGhpbmcgdGhhdCB3ZSYjODIxNztyZSB0ZXN0aW5nKS4=[Qq]

[f]WWVzLiBUaGUgcmF0ZSBvZiBsdW5nIGNhbmNlciBpcyB0aGUgZGVwZW5kZW50IHZhcmlhYmxlIChpdCYjODIxNztzIHdoYXQmIzgyMTc7cyBjYXVzZWQgYnkgdGhlIGluZGVwZW5kZW50IHZhcmlhYmxlLCB3aGljaCBpcyB0b2JhY2NvIHNtb2tlLg==[Qq]

4. Scientific Method and Experimental Design Flashcards

To make sure you understand the key terms we’ve used in this lesson, work through these flashcards. Flashcards can feel very difficult, but they’re incredibly effective in helping you to remember what you’ve learned. Be very honest with yourself as you use these cards. It’s much better to study a card twice than to rush through without learning the material.

Click here to start flashcard deck [qdeck style=”width: 528px; border: 2px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments Flashcards”]

[h] Flashcards: The Scientific Method and Controlled Experiments

[i] Instructions.

• Click ‘Flip’ to see the answer to each card.
• If you know it, click ‘Got it.”
• If you don’t know it as well as you’d like, click ‘Need more practice,’ and that card will go to the bottom of the deck so you can practice it again.
• ‘Shuffle’ lets you shuffle the deck.

[!]Card 1++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q] The step in the scientific method that involves sensing the world, and noticing patterns and relationships is  [textentry]

[a]The step in the scientific method that involves sensing the world, and noticing patterns and relationships is observation.

[!] CARD 2++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]An educated guess that includes a prediction is a _______________

[textentry] [a]An educated guess that includes a prediction is a hypothesis .

[!] CARD 3++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A structured form of observation that allows you to examine one thing at a time is a(n) _______________

[textentry] [a]A structured form of observation that allows you to examine one thing at a time is a(n) experiment

[!] CARD 5++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]An experiment tests the validity (or correctness) of a(n) _______________

[textentry] [a]An experiment tests the validity of a hypothesis .

[!] CARD 6++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A well-formulated hypothesis includes a __________

[textentry] [a]A well-formulated hypothesis includes a  prediction

[!] CARD 7++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]The thing you test in an experiment is the _________

[textentry] [a]The thing you test in an experiment is the  independent variable

[!] CARD 8++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]The measured or observed result of the independent variable is the ___________

[textentry] [a]The measured or observed result of the independent variable is the  dependent variable.

[!] CARD 9++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A student performs an experiment to test the effect of red light on plant growth. The independent variable is ________

[textentry]

[a]A student performs an experiment to test the effect of red light on plant growth. The independent variable is  red light

[!] CARD 10++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. What would be a logical control group?

[a]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. A logical control group would be  plants exposed to normal light.

[!] CARD 11++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++[/!]

[q]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. What would be a logical experimental group?

[a]A student performs an experiment to test the effect of red light on plant growth. The student’s hypothesis is that red light will produce more growth than normal light. A logical experimental group would be  plants exposed to red light.

If you want more practice, please press the restart button below. Otherwise, follow the links below. [restart] [/qdeck]

5. A controlled experiment to test the smoking/cancer connection

So, how would this work in the case of an animal experiment to test the hypothesis that tobacco smoke causes cancer?

Well, if it’s an animal experiment, we need an animal.

Like humans, rats are mammals. Their internal organs, including their lungs, look very much like miniature versions of those in humans. In terms of body chemistry, they’re also very much like us: many of the chemical reactions occurring in our cells are identical. So the reasoning (which is widely accepted in biology) is that if something causes cancer in a rat, it is likely to cause cancer in a human being.

[qwiz style = “width: 528px; min-height:0px; border: 3px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: Quiz 2″]

[h]Using the Scientific method

[q]So here’s our experiment. We’re going to have two rats. In one group, we’ll have a rat that smokes. In the second group, we’ll have a rat that’s exposed to exactly the same conditions (the same food, temperature, etc.). The only difference is that the second rat won’t smoke.

What’s the problem with this experiment?

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[q]So, here’s what we’re going to do: We’re going to use two groups of rats, each with enough individuals to  show the effect of the independent variable. One group will be exposed to tobacco smoke. A second group will be kept under identical conditions, except for the fact that it won’t be exposed to tobacco smoke. We’re going to measure the rate of cancer in each group, and see if there’s a difference.

If there is a difference, we can be pretty sure that it’s a result of the presence of the independent variable (tobacco smoke). This difference, because it depends on the effect of the independent variable, is called the dependent variable.

What’s the control group in this experiment?

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What’s the experimental group in this experiment?

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What’s the dependent variable in this experiment?

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[q]What’s the independent variable in this experiment?

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6. What Happened Next

Animal studies like the one described above confirmed the hypothesis that rats exposed to tobacco smoke will have higher rates of cancer. In fact, this had been known since the 1930s, when controlled experiments showed that elements of tobacco smoke, when put into liquid form, could cause tumors to form on the skin of rabbits.

Throughout the 1900s, several lines of evidence confirmed the tobacco/cancer link. These lines of evidence included

• Chemical analysis of tobacco to identify cancer-causing agents,
• Studies of how cells in lung tissue were affected by smoking, and
• Public health studies showing that people who smoked were more likely to develop lung cancer.

However, through much of the 1900s, smoking continued to increase among many populations around the world. This was largely caused by tobacco companies, which continued to market cigarettes, and which devoted significant amounts of resources to denying the scientific evidence about the danger of smoking. You can read the entire story by following the links at the bottom of this tutorial.

7. Checking Understanding Quiz

In this tutorial, we’ve learned about

• Hypothesize
• Draw conclusions
• independent variable
• dependent variable
• control group
• experimental group
• It tests only one thing (the independent variable)
• It uses large enough groups to avoid random results based on individual differences.

To make sure you’ve mastered this material, take the quiz below.

[qwiz style = “border: 3px solid black; ” qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: Checking Understanding”]

[h]Quiz: The Scientific Method and Designing Experiments [i] Here’s how the quiz works:

• Each question is multiple-choice, but the entire quiz is like a series of flashcards.
• If you get the question right, it comes off the deck.
• If you get the question wrong, it goes to the bottom of the deck, so you can try it again.

[q] Noticing patterns in the world around you is best classified as

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[q] An educated guess that includes a prediction is a(n)

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[q] A structured form of observation that allows you to observe one thing at a time is a(n)

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[q] This includes a prediction, and is best put in an “if…then…” format

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[q] This part of the scientific method involves testing whether a hypothesis is correct.

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[q]In an experiment, the thing you’re testing is the

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[q]In an experiment, the measured result is the

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[q]The part of the experiment that serves as a standard for comparison, and which shows you what the result would be without the independent variable, is the

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[q]Two students have designed an experiment to test the effect of loud bass notes on reproduction rates in guppies (a small aquarium fish). They divide the guppies into two groups of 15, each group in its own 20-gallon aquarium tank. One tank is exposed to the loud bass notes, and one is not.

In this experiment, which of the following is the independent variable?

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[q]Two students have designed an experiment to test the effect of low bass notes on reproduction rates in guppies (a small aquarium fish). They divide the guppies into two groups of 15, each group in its own 20-gallon aquarium tank. One tank is exposed to the low bass notes, and one is not.

In this experiment, which of the following is the dependent variable?

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In this experiment, which of the following is the control group ?

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In this experiment, which of the following is the experimental group ?

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[q]Bob wants to test whether lemon juice can keep dandelion weeds from growing in his garden. He creates several solutions of lemon juice. He then takes dandelion seeds and sprouts them on paper towels. Each day, he sprays the same amount of each solution on the seeds. The data are shown above.

Based on the data, what’s the problem with the design of Bob’s experiment

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[q]Clara is testing whether iron pills will help skinny dogs gain weight. For her experiment, she takes three dogs, a poodle, a boxer, and a collie. She adds iron to their food for two weeks and then records their weight. Here are her results

Based on the data, what’s the problem with the design of her experiment

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If you want to take this quiz again, click the button below

[/qwiz] If you need more practice, please scroll up to the top and work through this tutorial again. Otherwise, follow the links below:

8. The Scientific Method Song: Interactive Lyrics

This is an interactive reading of the lyrics to the Scientific Method Song . If you’re completing this tutorial on your own, and you want to watch the video, then click here  (the link will open in a new tab). But if you’re in class, please check with your teacher first!

[qwiz qrecord_id=”sciencemusicvideosMeister1961-Controlled Experiments: Scientific Method Song, Interactive Lyrics”]

[h]Interactive Lyrics, Scientific Method Song

[q labels=”top”]

Science always begins with a ___________ Inspired by an ___________ , Next step, as you might surmise, Is to take your question and hypothesize,

A _____________ should include a prediction, An educated guess in a form of “if … then” Like if science rapping is a memory aid Then better retention will be displayed.

Now hypothesis set, you’re ready for next step Performance of an experiment, The independent variable’s what you __________ _____________ variable’s the result you get

[l] dependent

[l] observation

[l] question

[l] experiment

[l] hypothesize

[l] observe   

Now science well-done’s about taking  __________

Because clear results, that’s your ultimate goal.

To see if what you’re testing is the _______  of an effect,

Your design has to be perfect.

Use two groups: __________ and experimental: Experimental gets your independent variable Control group’s the same except for one move: The independent ____________ gets ______________ .

Like to prove tobacco smoke is a cause of cancer, A good experiment will bring you the answer, Take two groups of guinea pigs or rats to test And make the groups ______ , that’s statistically best

[l] control

[l] removed

[l] variable

You gotta make ’em big, cause there’s always random stuff, So a small group of ____________ is never enough! You can get cancer even though you’ve never smoked But a single __________ , well that’s just an anecdote.

So set up two cages exactly the same, Controlling variables is the name of the game, Experimental group to smoke gets exposed, Cause that’s the _______________ variable you proposed.

[l] independent

[l] subjects

[q] BRIDGE : But I’m not saying science is always the way to get to the  _______ It won’t tell you whom to ______  or what path to pursue But amidst all this superstition and deceit It gives you a path to consult To cut through all the lies and confusion, And help you to come to your own  __________

[l] conclusion

[l] difference

[l] examine

And sure it was second-hand smoke that you tested, So maybe your results will be ____________ . This happens to scientists all of the time, Whenever there’s a __________ in their design.

Last step: try to publish in a scientific ________________ , As you try to win science fame eternal. It’s a never-ending process, and it’s awfully demanding. But that’s how we build scientific  ___________________

[l] contested

[l] journal

[l] understanding

9. Next steps (reading about “The Shameful Past…”)

• Click the following link to read The Shameful Past: The history of the discovery of the cigarette-cancer link . ” This is the reading on page 3 of the student learning guide that goes with this module.
• Return to the menu for Module 1: Biology, Core Concepts
• Use the menu choices above to choose another module.

• Controlled Experiments: Methods, Examples & Limitations

What happens in experimental research is that the researcher alters the independent variables so as to determine their impacts on the dependent variables. 

Therefore, when the experiment is controlled, you can expect that the researcher will control all other variables except for the independent variables . This is done so that the other variables do not have an influence on the dependent variables. 

In this article, we are going to consider controlled experiment, how important it is in a study, and how it can be designed. But before we dig deep, let us look at the definition of a controlled experiment.

What is a Controlled Experiment?

In a scientific experiment, a controlled experiment is a test that is directly altered by the researcher so that only one variable is studied at a time. The single variable being studied will then be the independent variable.

This independent variable is manipulated by the researcher so that its effect on the hypothesis or data being studied is known. While the researcher studies the single independent variable, the controlled variables are made constant to reduce or balance out their impact on the research.

To achieve a controlled experiment, the research population is mostly distributed into two groups. Then the treatment is administered to one of the two groups, while the other group gets the control conditions. This other group is referred to as the control group.

The control group gets the standard conditions and is placed in the standard environment and it also allows for comparison with the other group, which is referred to as the experimental group or the treatment group. Obtaining the difference between these two groups’ behavior is important because in any scientific experiment, being able to show the statistical significance of the results is the only criterion for the results to be accepted.  

So to determine whether the experiment supports the hypothesis, or if the data is a result of chance, the researcher will check for the difference between the control group and experimental group. Then the results from the differences will be compared with the expected difference.

For example, a researcher may want to answer this question, do dogs also have a music taste? In case you’re wondering too, yes, there are existing studies by researchers on how dogs react to different music genres. 

Back to the example, the researcher may develop a controlled experiment with high consideration on the variables that affect each dog. Some of these variables that may have effects on the dog are; the dog’s environment when listening to music, the temperature of the environment, the music volume, and human presence. 

The independent variable to focus on in this research is the genre of the music. To determine if there is an effect on the dog while listening to different kinds of music, the dog’s environment must be controlled. A controlled experiment would limit interaction between the dog and other variables. 

In this experiment, the researcher can also divide the dogs into two groups, one group will perform the music test while the other, the control group will be used as the baseline or standard behavior. The control group behavior can be observed along with the treatment group and the differences in the two group’s behavior can be analyzed. 

What is an Experimental Control?

Experimental control is the technique used by the researcher in scientific research to minimize the effects of extraneous variables. Experimental control also strengthens the ability of the independent variable to change the dependent variable.

For example, the cause and effect possibilities will be examined in a well-designed and properly controlled experiment if the independent variable (Treatment Y) causes a behavioral change in the dependent variable (Subject X).

In another example, a researcher feeds 20 lab rats with an artificial sweetener and from the researcher’s observation, six of the rats died of dehydration. Now, the actual cause of death may be artificial sweeteners or an unrelated factor. Such as the water supplied to the rats being contaminated or the rats could not drink enough, or suffering a disease. 

Read: Nominal, Ordinal, Interval & Ratio Variable + [Examples]

For a researcher, eliminating these potential causes one after the other will consume time, and be tedious. Hence, the researcher can make use of experimental control. This method will allow the researcher to divide the rats into two groups: one group will receive the artificial sweetener while the other one doesn’t. The two groups will be placed in similar conditions and observed in similar ways. The differences that now occur in morbidity between the two groups can be traced to the sweetener with certainty.

From the example above, the experimental control is administered as a form of a control group. The data from the control group is then said to be the standard against which every other experimental outcome is measured.

Purpose & Importance of Control in Experimentation

1. One significant purpose of experimental controls is that it allows researchers to eliminate various confounding variables or uncertainty in their research. A researcher will need to use an experimental control to ensure that only the variables that are intended to change, are changed in research.  

2. Controlled experiments also allow researchers to control the specific variables they think might have an effect on the outcomes of the study. The researcher will use a control group if he/she believes some extra variables can form an effect on the results of the study. This is to ensure that the extra variable is held constant and possible influences are measured.  

3. Controlled experiments establish a standard that the outcome of a study should be compared to, and allow researchers to correct for potential errors. 

Read more: What are Cross-Sectional Studies: Examples, Definition, Types

Methods of Experimental Control

Here are some methods used to achieve control in experimental research

• Use of Control Groups

Control groups are required for controlled experiments. Control groups will allow the researcher to run a test on fake treatment, and comparable treatment. It will also compare the result of the comparison with the researcher’s experimental treatment. The results will allow the researcher to understand if the treatment administered caused the outcome or if other factors such as time, or others are involved and whether they would have yielded the same effects.  

For an example of a control group experiment, a researcher conducting an experiment on the effects of colors in advertising, asked all the participants to come individually to a lab. In this lab,  environmental conditions are kept the same all through the research.

For the researcher to determine the effect of colors in advertising, each of the participants is placed in either of the two groups: the control group or the experimental group.

In the control group, the advertisement color is yellow to represent the clothing industry while blue is given as the advertisement color to the experimental group to represent the clothing industry also. The only difference in these two groups will be the color of the advertisement, other variables will be similar.

• Use of Masking (blinding)

Masking occurs in an experiment when the researcher hides condition assignments from the participants.  If it’s double-blind research, both the researcher and the participants will be in the dark. Masking or blinding is mostly used in clinical studies to test new treatments.

Masking as a control measure takes place because sometimes, researchers may unintentionally influence the participants to act in ways that support their hypotheses. In another scenario, the goal of the study might be revealed to the participants through the study environment and this may influence their responses.

Masking, however, blinds the participants from having a deeper knowledge of the research whether they’re in the control group or the experimental group. This helps to control and reduce biases from either the researcher or the participants that could influence the results of the study.

• Use of Random Assignment

Random assignment or distribution is used to avoid systematic differences between participants in the experimental group and the control group. This helps to evenly distribute extraneous participant variables, thereby making the comparison between groups valid. Another usefulness of random assignment is that it shows the difference between true experiments from quasi-experiments.

Learn About: Double-Blind Studies in Research: Types, Pros & Cons

How to Design a Controlled Experiment

For a researcher to design a controlled experiment, the researcher will need:

• A hypothesis that can be tested.
• One or more independent variables can be changed or manipulated precisely.
• One or more dependent variables can be accurately measured.

Then, when the researcher is designing the experiment, he or she must decide on:

• How will the variables be manipulated?
• How will control be set up in case of any potential confounding variables?
• How large will the samples or participants included in the study be?
• How will the participants be distributed into treatment levels?

How you design your experimental control is highly significant to your experiment’s external and internal validity.

Controlled Experiment Examples

1. A good example of a controlled group would be an experiment to test the effects of a drug. The sample population would be divided into two, the group receiving the drug would be the experimental group while the group receiving the placebo would be the control group (Note that all the variables such as age, and sex, will be the same).

The only significant difference between the two groups will be the taking of medication. You can determine if the drug is effective or not if the control group and experimental group show similar results. 

2. Let’s take a look at this example too. If a researcher wants to determine the impact of different soil types on the germination period of seeds, the researcher can proceed to set up four different pots. Each of the pots would be filled with a different type of soil and then seeds can be planted on the soil. After which each soil pot will be watered and exposed to sunlight.

The researcher will start to measure how long it took for the seeds to sprout in each of the different soil types. Control measures for this experiment might be to place some seeds in a pot without filling the pot with soil. The reason behind this control measure is to determine that no other factor is responsible for germination except the soil.

Here, the researcher can also control the amount of sun the seeds are exposed to, or how much water they are given. The aim is to eliminate all other variables that can affect how quickly the seeds sprouted. 

Experimental controls are important, but it is also important to note that not all experiments should be controlled and It is still possible to get useful data from experiments that are not controlled.

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Problems with Controlled Experiments

It is true that the best way to test for cause and effect relationships is by conducting controlled experiments. However, controlled experiments also have some challenges. Some of which are:

• Difficulties in controlling all the variables especially when the participants in your research are human participants. It can be impossible to hold all the extra variables constant because all individuals have different experiences that may influence their behaviors.
• Controlled experiments are at risk of low external validity because there’s a limit to how the results from the research can be extrapolated to a very large population .
• Your research may lack relatability to real world experience if they are too controlled and that will make it hard for you to apply your outcomes outside a controlled setting.

Control Group vs an Experimental Group

There is a thin line between the control group and the experimental group. That line is the treatment condition. As we have earlier established, the experimental group is the one that gets the treatment while the control group is the placebo group.

All controlled experiments require control groups because control groups will allow you to compare treatments, and to test if there is no treatment while you compare the result with your experimental treatment.

Therefore, both the experimental group and the control group are required to conduct a controlled experiment

FAQs about Controlled Experiments

• Is the control condition the same as the control group?

The control group is different from the control condition. However, the control condition is administered to the control group. 

• What are positive and negative control in an experiment?

The negative control is the group where no change or response is expected while the positive control is the group that receives the treatment with a certainty of a positive result.

While the controlled experiment is beneficial to eliminate extraneous variables in research and focus on the independent variable only to cause an effect on the dependent variable.

Researchers should be careful so they don’t lose real-life relatability to too controlled experiments and also, not all experiments should be controlled.

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Experimental Design - Independent, Dependent, and Controlled Variables

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Scientific experiments are meant to show cause and effect of a phenomena (relationships in nature).  The “ variables ” are any factor, trait, or condition that can be changed in the experiment and that can have an effect on the outcome of the experiment.

An experiment can have three kinds of variables: i ndependent, dependent, and controlled .

• The independent variable is one single factor that is changed by the scientist followed by observation to watch for changes. It is important that there is just one independent variable, so that results are not confusing.
• The dependent variable is the factor that changes as a result of the change to the independent variable.
• The controlled variables (or constant variables) are factors that the scientist wants to remain constant if the experiment is to show accurate results. To be able to measure results, each of the variables must be able to be measured.

For example, let’s design an experiment with two plants sitting in the sun side by side. The controlled variables (or constants) are that at the beginning of the experiment, the plants are the same size, get the same amount of sunlight, experience the same ambient temperature and are in the same amount and consistency of soil (the weight of the soil and container should be measured before the plants are added). The independent variable is that one plant is getting watered (1 cup of water) every day and one plant is getting watered (1 cup of water) once a week. The dependent variables are the changes in the two plants that the scientist observes over time.

Can you describe the dependent variable that may result from this experiment? After four weeks, the dependent variable may be that one plant is taller, heavier and more developed than the other. These results can be recorded and graphed by measuring and comparing both plants’ height, weight (removing the weight of the soil and container recorded beforehand) and a comparison of observable foliage.

Using What You Learned: Design another experiment using the two plants, but change the independent variable. Can you describe the dependent variable that may result from this new experiment?

Think of another simple experiment and name the independent, dependent, and controlled variables. Use the graphic organizer included in the PDF below to organize your experiment's variables.

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Controlled Experiment Meaning, Importance & Examples in Science

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A controlled experiment is a research method that tests a hypothesis by manipulating a specific variable, called the independent variable. Researchers keep all other factors constant (controlled) to see how the independent variable affects the outcome, or dependent variable. Control groups are used for comparison, so that any changes can be attributed to the independent variable. A controlled scientific experiment helps establish cause-and-effect relationships and reduces potential bias, leading to more reliable results.

Any study in psychology, sociology, natural sciences and humanities is impossible without conducting experiments. They confirm theories, test new drugs, and develop methods. Besides, students often have to control an experiment while learning.

A controlled scientific experiment — how does it proceed? What determines accuracy and reliability of results? What methods are used by  researchers? We will take a closer look at te definition of a controlled experiement. Read our guide to learn how to rule out mistakes and outside influences in your experiment. You will find many useful suggestions in this article, including tips on how to provide control, exclude an influence of extraneous factors and many more.

What Is a Controlled Experiment: Definition

A controlled experiment is testing under programmed conditions. It’s the main tool for testing advanced scientific theories. Validity and effectiveness of scientific research depend on the experiment’s accuracy. This method is actively used in medicine. It is also used in social and natural sciences, psychology, and biochemistry. There are two main parts of such an experiment:

• test factor
• experimental and control groups.

External influences on both groups must remain constant. Experimental group help researchers test substances or effects. Control group is not affected by this effect. Experimenter observes an influence of independent variables on dependent variables. Excluding extraneous influences ensures that you receive statistically valid results.

Importance of Control in an Experiment

Extraneous variables should not affect the course of an experiment. The role of a control in an experiment is to exclude external factors and ensure high internal validity of results. The main purpose is to eliminate outside influences. And also you should be able to maximally manage an effect of an independent variable. That makes it possible to exclude mistaken hypotheses about an observed effect. At the same time, it is necessary to ensure high internal validity. It means measuring the exact impact of an independent variable on a dependent one. External validity is an ability to transfer test results outside the research framework. Before doing such kind of an experiment, find out the difference between reliability and validity beforehand.

Examples of Controlled Experiments

Several interrelated variables can be examined in a single study. Controlled experiments explore relationships between people. They also explore altered states of consciousness or medication effects. Distribution of participants should be made randomly. It should be done to exclude an influence of external factors. Consider controlled experiment example in somnology. For example, the effect of sleep duration on concentration is being investigated. A study may include assessing different sleep duration effects. Dependent variable is an ability to concentrate as measured by cognitive tests results. Independent variable is sleep duration. Statistical measurement methods will determine changes in concentration of a person's attention depending on a sleep duration. So what is controlled in this experiment? Any external factors that may distort the relationship between independent and dependent variables .

Methods Used in Controlled Experiments

Choosing methods depends on controlled experiment conditions. Besides, a research on new medications is being conducted on volunteers. Consider these methods of forming samples of groups:

• Parallel Each object of research is assigned randomly. Everyone is influenced by factor being investigated.
• Crossover Each participant is influenced by independent variable in a random sequence.
• Cluster Previously established groups of objects are investigated.
• Factorial Distribution of objects influenced in group occurs randomly.

A laboratory test provides maximum experimental control. It allows you to standardize sampling conditions and reproduce identical conditions for subsequent experiments.

Randomized Controlled Experiment

It is necessary to see the difference between controlled experiments and quasi-experiments. The latter does not give a real picture of the phenomenon under study. Random assignments ensure that an experimental study is objective. Each subject receives an equal opportunity for experiment. Random selection allows you to compose a large population of participants in an experiment.  If principles of random distribution are violated, then we have quasi experiment . Its results can be predicted in advance and they are not reliable.

Control Group in an Experiment

Scientific research suggests the need to compare tests and experiments results with behavior of a control group. This is especially important when you conduct medical test on effects of treatments and new drugs. Comparison of control and experimental groups ’ well-being allows one to draw conclusions about taking some drug. In the control group, changes may also occur against the background of taking a placebo. Precise monitoring is essential to distinguish treatment outcomes from psychological factors.

Blinding in an Experiment

In medicine, the most reliable method is double-blind placebo-controlled experiment. When conducting it, not only participants, but also researchers do not know about distribution into groups. This ensures that all participants in experiment behave naturally. They eliminate bias.  Experimental group gets test drug during course of the study. If patients cannot do without treatment, they are given a drug of proven action. Control group gets a placebo, masking some real medicine.

Pros and Cons of a Controlled Experiment

The advantage of controlled experiment is:

• Demonstrable cause-and-effect relationship between an investigated factor and its influence on experimental group;
• Possibility to exclude external variables;
• Impact of the researcher’s bias is ruled out;
• Ability to study random groups of participants;
• Test results can be verified;
• Data can be combined with results from other studies.

These advantages are necessary to ensure an external validity of results.

The disadvantages are:

• Attempts to manage numerous variables is time-consuming and requires many precise data;
• There are huge numbers of variables and managing all variables is almost impossible;
• Researcher’s personal bias may intrude;
• Groups may not be comparable;
• Human response can be difficult to measure;
• Results may only apply to one situation and may be difficult to replicate.

Such tests have their disadvantages, so scientists and researchers should find a balance between the benefits it provides and the drawbacks it presents.

Bottom Line

Summing up, it is necessary to emphasize the relevance of control science experiments. Not all companies, nor all private researchers have opportunity to organize a large-scale experiment.  The theory confirmation in psychology, sociology, medicine, biochemistry is impossible without experimental research. Among these, it is the most reliable method for predicting possible outcomes. The experimental techniques limit the influence of extraneous effects. They also limit an observer's intervention during a test.

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FAQ About Controlled Experiments

1.why is a control group important in an experiment.

The purpose of a control group in an experiment is to provide a basis for comparing and analyzing effects of an investigated factor on participants in experimental group. It allows you to eliminate an impact of fatal external factors on independent and dependent variables. An experimental group is influenced by an investigated factor. At this time, the control group allows you to assess the progress of the ongoing processes.

2. What is the control in an experiment?

Scientific control in an experiment is necessary to minimize the extraneous variables' influence. It allows you to exclude an impact of an element that is not directly related to essence of a study. It helps focus the attention on the influence of an independent variable. Experimental and control groups comparison prevent errors. It also eliminates observer bias.

3. Why are hypotheses important to controlled experiments?

A controlled experiment's purpose is to confirm or disprove a particular hypothesis. It sets the research direction, allows you to choose methods and highlight important factors. It ensures accuracy of the result, and excludes extraneous influences. The bounded stage allows you to assess the effect of a variable on a control group. Hypotheses are important to experiments as a basis for creating a work plan.

4. What is the difference between a control group and an experimental group?

Experimental group is influenced by an investigated independent variable. This receives the treatment whose effect researchers wish to study. For example, experimenters are testing a new drug’s effectiveness. Whereas a control group does not receive this treatment. Both groups are recruiting volunteers with the same disease. They also should be identical in all other ways. To prevent control group from suffering from a lack of treatment, participants are given previously tested drugs. Experimenters monitor the effects of old and new drugs and compare them.

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What Is A Controlled Experiment? Aren’t All Experiments Controlled?

Why should you experiment, how should you experiment, key parameters of a controlled experiment, is there such a thing as an uncontrolled experiment.

A procedure that helps you understand the influence of various factors that affect a result and the extent of their effect in a controlled environment.

Have you ever done science experiments that have numerous parameters you need to take care of to get an accurate result?

If so, I know exactly how that feels!

Most of the time, you won’t get a perfect value, but rather a value that is nearly correct. It can be so frustrating at times, as you need to take care of the amount of catalyst, the temperature, pressure and a million other things!

I wonder who found out that you need precisely ‘this’ thing in exactly ‘this’ amount to get ‘that’ thing! Well, over time, I’ve realized just how much important these parameters are. These values help us set up a controlled environment where the experiment can occur.

And while many people loathe doing lengthy experiments, scientists have performed these exact same experiments a million times to find the perfect mix of parameters that give a predictable result! Now that’s perseverance!!

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There was a time when scientists speculated about plants being alive in the same way as humans. Jagdish Chandra Bose was the scientist who was able to prove that plants are indeed living things by noting their response to different stimuli. He used an experiment wherein the roots of a plant’s stem were dipped in a solution of Bromine Chloride, a poison . He observed the pulse of the plant as a white spot on the crescograph, a device that could magnify the motion of plant tissues up to 10,000 times.

This experiment may have been groundbreaking at that time, but his result was derived because of the three steps that every scientist follows to arrive at a conclusion.

• Scientists observe a certain phenomenon that interests them or sparks their curiosity.
• They form a hypothesis, i.e., they try to establish a ‘cause-effect’ relationship for the phenomenon. There are multiple hypotheses for a single occurrence that may or may not be correct.

         Example: the atomic model was proposed by many scientists before the most recent Quantum model was accepted. Simply put, a hypothesis is the possible cause of the effect that one wishes to study.

• Now, the hypothesis is often based on mathematical calculations or general observations, but until they are disproved, the theory is not accepted.
• This is where experiments come into the picture. Various experiments are done that can support the hypothesis. If a particular theory is supported by experimental backing, the hypothesis becomes a “scientific theory/discovery”.

Also Read: What Is Endogeneity? What Is An Exogenous Variable?

To reach effective results, you need to test your hypothesis by performing an experiment, but it’s not as if any random experiment can give you results. A controlled experiment allows you to isolate and study the clear result that will eventually allow you to draw conclusions.

A single phenomenon is the result of multiple factors, but how do you know the independent effect of each factor? A controlled experiment basically limits the scope of the result because only one or two factors affecting the result are allowed to vary. All the other factors are kept constant.

Also Read: What Is An Independent Variable?

Now, when you perform an experiment, you’re basically looking for two things

• The factors that affect the final result.
• The extent to which each factor contributes to the result.

We can identify the elements that affect the result by keeping all the other elements constant. These variables/factors that are constant are known as control variables/constant variables .

If we want to test the effect of a certain (factor) fertilizer on plants, we take two plants, both identical in all respects, such that all the other factors affecting its growth remain constant. Now, to one plant we add the fertilizer, and to the other, we add no fertilizer. Thus, after the allotted time period, if the fertilizer was actually useful, you will see that the growth in one plant is greater than the other. Here, the plant that got the fertilizer is the experimental group and the one without the fertilizer is the control group .

If you’re wondering what the use of the control group is, it basically provides you with a minimal value to start with. It allows you to compare the effect of the fertilizer with respect to the normal growth factor and the extent to which the fertilizer enhanced the growth of the plant. A controlled experiment tries to form a link between the cause and the effect. If we are to study the effect of fertilizers on plant growth, the cause will be the ‘fertilizer’ and its effect would be the ‘growth of the plant’. In other words:

• The fertilizer would be the independent variable — a variable that is changed and modified to study its effect.
• The growth of the plant will be the dependent variable— a variable that is being tested and whose value depends on the independent variable.

Well, after reading all of this, it’s pretty obvious that controlled experiments are often set up that way and don’t occur naturally. They also give results that are reliable and spot on!

Clearly, experiments that don’t have any control variables are uncontrolled in every way. In fact, the entire natural phenomenon that gave rise to a scientist’s hypothesis is an uncontrolled experiment. This implies that, without control, you can still get results, but those results are unclear. You can draw conclusions from uncontrolled experiments, but it’s a lot harder to determine the true influence of individual factors when all of them are acting at the same time.

Some experiments, however, are impossible to control! Experiments that require testing on humans are influenced by genetic makeup, metabolism and psychology, among other factors, all of which are beyond human control. Thus, there is often a result that is simply averaged and used because no particular result can reflect the whole effect.

Uncontrolled experiments may not give perfect results, but they often help scientists observe patterns. A task that was performed better by more females than males helps to identify that there is possibly an element of female psychology, a hormone or temperament that influenced the result.

Controlled experimentation is the most widely preferred method used to study and prove a hypothesis. Nature is an intelligent experimenter and designs phenomena that are intricate and detailed, and we humans are still trying to understand those details, so we need to break things into parts before we can understand the whole picture. This is where controlled experimentation helps us. All in all, controlled experimentation aids us in understanding things at a pace we are comfortable with, while giving us time to explore the depths to which we want to study a given occurrence.

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Zankhana has completed her Bachelors in Electronics and Telecommunications Engineering. She is an avid reader of works of mythology and history. She is trained in Hindustani Classical Singing and Kathak. She likes to travel and trusts her artsy heart and scientific mind to take her to places that she has dreamt of.

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Module 2: Research Design - Section 2

• Section 1 Discussion
• Section 2 Discussion

Section 2: Experimental Studies

Unlike a descriptive study, an experiment is a study in which a treatment, procedure, or program is intentionally introduced and a result or outcome is observed. The American Heritage Dictionary of the English Language defines an experiment as "A test under controlled conditions that is made to demonstrate a known truth, to examine the validity of a hypothesis, or to determine the efficacy of something previously untried."

This means that no matter who the participant is, he/she has an equal chance of getting into all of the groups or treatments in an experiment. This process helps to ensure that the groups or treatments are similar at the beginning of the study so that there is more confidence that the manipulation (group or treatment) "caused" the outcome. More information about random assignment may be found in section Random assignment.

Definition : An experiment is a study in which a treatment, procedure, or program is intentionally introduced and a result or outcome is observed.

Case Example for Experimental Study

Experimental studies — example 1.

Experimental Studies — Example 2

A fitness instructor wants to test the effectiveness of a performance-enhancing herbal supplement on students in her exercise class. To create experimental groups that are similar at the beginning of the study, the students are assigned into two groups at random (they can not choose which group they are in). Students in both groups are given a pill to take every day, but they do not know whether the pill is a placebo (sugar pill) or the herbal supplement. The instructor gives Group A the herbal supplement and Group B receives the placebo (sugar pill). The students' fitness level is compared before and after six weeks of consuming the supplement or the sugar pill. No differences in performance ability were found between the two groups suggesting that the herbal supplement was not effective.

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Control Group vs Experimental Group

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BA (Hons) Psychology, Princeton University

Julia Simkus is a graduate of Princeton University with a Bachelor of Arts in Psychology. She is currently studying for a Master's Degree in Counseling for Mental Health and Wellness in September 2023. Julia's research has been published in peer reviewed journals.

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Editor-in-Chief for Simply Psychology

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On This Page:

In a controlled experiment , scientists compare a control group, and an experimental group is identical in all respects except for one difference – experimental manipulation.

Differences

Unlike the experimental group, the control group is not exposed to the independent variable under investigation. So, it provides a baseline against which any changes in the experimental group can be compared.

Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between the two are due to experimental manipulation rather than chance.

Almost all experimental studies are designed to include a control group and one or more experimental groups. In most cases, participants are randomly assigned to either a control or experimental group.

Because participants are randomly assigned to either group, we can assume that the groups are identical except for manipulating the independent variable in the experimental group.

It is important that every aspect of the experimental environment is the same and that the experimenters carry out the exact same procedures with both groups so researchers can confidently conclude that any differences between groups are actually due to the difference in treatments.

Control Group

A control group consists of participants who do not receive any experimental treatment. The control participants serve as a comparison group.

The control group is matched as closely as possible to the experimental group, including age, gender, social class, ethnicity, etc.

The difference between the control and experimental groups is that the control group is not exposed to the independent variable , which is thought to be the cause of the behavior being investigated.

Researchers will compare the individuals in the control group to those in the experimental group to isolate the independent variable and examine its impact.

The control group is important because it serves as a baseline, enabling researchers to see what impact changes to the independent variable produce and strengthening researchers’ ability to draw conclusions from a study.

Without the presence of a control group, a researcher cannot determine whether a particular treatment truly has an effect on an experimental group.

Control groups are critical to the scientific method as they help ensure the internal validity of a study.

Assume you want to test a new medication for ADHD . One group would receive the new medication, and the other group would receive a pill that looked exactly the same as the one that the others received, but it would be a placebo. The group that takes the placebo would be the control group.

Types of Control Groups

Positive control group.

• A positive control group is an experimental control that will produce a known response or the desired effect.
• A positive control is used to ensure a test’s success and confirm an experiment’s validity.
• For example, when testing for a new medication, an already commercially available medication could serve as the positive control.

Negative Control Group

• A negative control group is an experimental control that does not result in the desired outcome of the experiment.
• A negative control is used to ensure that there is no response to the treatment and help identify the influence of external factors on the test.
• An example of a negative control would be using a placebo when testing for a new medication.

Experimental Group

An experimental group consists of participants exposed to a particular manipulation of the independent variable. These are the participants who receive the treatment of interest.

Researchers will compare the responses of the experimental group to those of a control group to see if the independent variable impacted the participants.

An experiment must have at least one control group and one experimental group; however, a single experiment can include multiple experimental groups, which are all compared against the control group.

Having multiple experimental groups enables researchers to vary different levels of an experimental variable and compare the effects of these changes to the control group and among each other.

Assume you want to study to determine if listening to different types of music can help with focus while studying.

You randomly assign participants to one of three groups: one group that listens to music with lyrics, one group that listens to music without lyrics, and another group that listens to no music.

The group of participants listening to no music while studying is the control group, and the groups listening to music, whether with or without lyrics, are the two experimental groups.

Frequently Asked Questions

1. what is the difference between the control group and the experimental group in an experimental study.

Put simply; an experimental group is a group that receives the variable, or treatment, that the researchers are testing, whereas the control group does not. These two groups should be identical in all other aspects.

2. What is the purpose of a control group in an experiment

A control group is essential in experimental research because it:

Provides a baseline against which the effects of the manipulated variable (the independent variable) can be measured.

Helps to ensure that any changes observed in the experimental group are indeed due to the manipulation of the independent variable and not due to other extraneous or confounding factors.

Helps to account for the placebo effect, where participants’ beliefs about the treatment can influence their behavior or responses.

In essence, it increases the internal validity of the results and the confidence we can have in the conclusions.

3. Do experimental studies always need a control group?

Not all experiments require a control group, but a true “controlled experiment” does require at least one control group. For example, experiments that use a within-subjects design do not have a control group.

In  within-subjects designs , all participants experience every condition and are tested before and after being exposed to treatment.

These experimental designs tend to have weaker internal validity as it is more difficult for a researcher to be confident that the outcome was caused by the experimental treatment and not by a confounding variable.

4. Can a study include more than one control group?

Yes, studies can include multiple control groups. For example, if several distinct groups of subjects do not receive the treatment, these would be the control groups.

5. How is the control group treated differently from the experimental groups?

The control group and the experimental group(s) are treated identically except for one key difference: exposure to the independent variable, which is the factor being tested. The experimental group is subjected to the independent variable, whereas the control group is not.

This distinction allows researchers to measure the effect of the independent variable on the experimental group by comparing it to the control group, which serves as a baseline or standard.

Bailey, R. A. (2008). Design of Comparative Experiments. Cambridge University Press. ISBN 978-0-521-68357-9.

Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.

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• Knowledge Base

Methodology

• Guide to Experimental Design | Overview, Steps, & Examples

Guide to Experimental Design | Overview, 5 steps & Examples

Published on December 3, 2019 by Rebecca Bevans . Revised on June 21, 2023.

Experiments are used to study causal relationships . You manipulate one or more independent variables and measure their effect on one or more dependent variables.

Experimental design create a set of procedures to systematically test a hypothesis . A good experimental design requires a strong understanding of the system you are studying.

There are five key steps in designing an experiment:

• Consider your variables and how they are related
• Write a specific, testable hypothesis
• Design experimental treatments to manipulate your independent variable
• Assign subjects to groups, either between-subjects or within-subjects
• Plan how you will measure your dependent variable

For valid conclusions, you also need to select a representative sample and control any  extraneous variables that might influence your results. If random assignment of participants to control and treatment groups is impossible, unethical, or highly difficult, consider an observational study instead. This minimizes several types of research bias, particularly sampling bias , survivorship bias , and attrition bias as time passes.

Table of contents

Step 1: define your variables, step 2: write your hypothesis, step 3: design your experimental treatments, step 4: assign your subjects to treatment groups, step 5: measure your dependent variable, other interesting articles, frequently asked questions about experiments.

You should begin with a specific research question . We will work with two research question examples, one from health sciences and one from ecology:

To translate your research question into an experimental hypothesis, you need to define the main variables and make predictions about how they are related.

Start by simply listing the independent and dependent variables .

Then you need to think about possible extraneous and confounding variables and consider how you might control  them in your experiment.

Finally, you can put these variables together into a diagram. Use arrows to show the possible relationships between variables and include signs to show the expected direction of the relationships.

Here we predict that increasing temperature will increase soil respiration and decrease soil moisture, while decreasing soil moisture will lead to decreased soil respiration.

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Now that you have a strong conceptual understanding of the system you are studying, you should be able to write a specific, testable hypothesis that addresses your research question.

The next steps will describe how to design a controlled experiment . In a controlled experiment, you must be able to:

• Systematically and precisely manipulate the independent variable(s).
• Precisely measure the dependent variable(s).
• Control any potential confounding variables.

If your study system doesn’t match these criteria, there are other types of research you can use to answer your research question.

How you manipulate the independent variable can affect the experiment’s external validity – that is, the extent to which the results can be generalized and applied to the broader world.

First, you may need to decide how widely to vary your independent variable.

• just slightly above the natural range for your study region.
• over a wider range of temperatures to mimic future warming.
• over an extreme range that is beyond any possible natural variation.

Second, you may need to choose how finely to vary your independent variable. Sometimes this choice is made for you by your experimental system, but often you will need to decide, and this will affect how much you can infer from your results.

• a categorical variable : either as binary (yes/no) or as levels of a factor (no phone use, low phone use, high phone use).
• a continuous variable (minutes of phone use measured every night).

How you apply your experimental treatments to your test subjects is crucial for obtaining valid and reliable results.

First, you need to consider the study size : how many individuals will be included in the experiment? In general, the more subjects you include, the greater your experiment’s statistical power , which determines how much confidence you can have in your results.

Then you need to randomly assign your subjects to treatment groups . Each group receives a different level of the treatment (e.g. no phone use, low phone use, high phone use).

You should also include a control group , which receives no treatment. The control group tells us what would have happened to your test subjects without any experimental intervention.

When assigning your subjects to groups, there are two main choices you need to make:

• A completely randomized design vs a randomized block design .
• A between-subjects design vs a within-subjects design .

Randomization

An experiment can be completely randomized or randomized within blocks (aka strata):

• In a completely randomized design , every subject is assigned to a treatment group at random.
• In a randomized block design (aka stratified random design), subjects are first grouped according to a characteristic they share, and then randomly assigned to treatments within those groups.

Sometimes randomization isn’t practical or ethical , so researchers create partially-random or even non-random designs. An experimental design where treatments aren’t randomly assigned is called a quasi-experimental design .

Between-subjects vs. within-subjects

In a between-subjects design (also known as an independent measures design or classic ANOVA design), individuals receive only one of the possible levels of an experimental treatment.

In medical or social research, you might also use matched pairs within your between-subjects design to make sure that each treatment group contains the same variety of test subjects in the same proportions.

In a within-subjects design (also known as a repeated measures design), every individual receives each of the experimental treatments consecutively, and their responses to each treatment are measured.

Within-subjects or repeated measures can also refer to an experimental design where an effect emerges over time, and individual responses are measured over time in order to measure this effect as it emerges.

Counterbalancing (randomizing or reversing the order of treatments among subjects) is often used in within-subjects designs to ensure that the order of treatment application doesn’t influence the results of the experiment.

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Finally, you need to decide how you’ll collect data on your dependent variable outcomes. You should aim for reliable and valid measurements that minimize research bias or error.

Some variables, like temperature, can be objectively measured with scientific instruments. Others may need to be operationalized to turn them into measurable observations.

• Ask participants to record what time they go to sleep and get up each day.
• Ask participants to wear a sleep tracker.

How precisely you measure your dependent variable also affects the kinds of statistical analysis you can use on your data.

Experiments are always context-dependent, and a good experimental design will take into account all of the unique considerations of your study system to produce information that is both valid and relevant to your research question.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Student’s  t -distribution
• Normal distribution
• Null and Alternative Hypotheses
• Chi square tests
• Confidence interval
• Cluster sampling
• Stratified sampling
• Data cleansing
• Reproducibility vs Replicability
• Peer review
• Likert scale

Research bias

• Implicit bias
• Framing effect
• Cognitive bias
• Placebo effect
• Hawthorne effect
• Hindsight bias
• Affect heuristic

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

• A testable hypothesis
• At least one independent variable that can be precisely manipulated
• At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

• How you will manipulate the variable(s)
• How you will control for any potential confounding variables
• How many subjects or samples will be included in the study
• How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

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What Is an Experiment? Definition and Design

The Basics of an Experiment

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• Ph.D., Biomedical Sciences, University of Tennessee at Knoxville
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Science is concerned with experiments and experimentation, but do you know what exactly an experiment is? Here's a look at what an experiment is... and isn't!

Key Takeaways: Experiments

• An experiment is a procedure designed to test a hypothesis as part of the scientific method.
• The two key variables in any experiment are the independent and dependent variables. The independent variable is controlled or changed to test its effects on the dependent variable.
• Three key types of experiments are controlled experiments, field experiments, and natural experiments.

What Is an Experiment? The Short Answer

In its simplest form, an experiment is simply the test of a hypothesis . A hypothesis, in turn, is a proposed relationship or explanation of phenomena.

Experiment Basics

The experiment is the foundation of the scientific method , which is a systematic means of exploring the world around you. Although some experiments take place in laboratories, you could perform an experiment anywhere, at any time.

Take a look at the steps of the scientific method:

• Make observations.
• Formulate a hypothesis.
• Design and conduct an experiment to test the hypothesis.
• Evaluate the results of the experiment.
• Accept or reject the hypothesis.
• If necessary, make and test a new hypothesis.

Types of Experiments

• Natural Experiments : A natural experiment also is called a quasi-experiment. A natural experiment involves making a prediction or forming a hypothesis and then gathering data by observing a system. The variables are not controlled in a natural experiment.
• Controlled Experiments : Lab experiments are controlled experiments , although you can perform a controlled experiment outside of a lab setting! In a controlled experiment, you compare an experimental group with a control group. Ideally, these two groups are identical except for one variable , the independent variable .
• Field Experiments : A field experiment may be either a natural experiment or a controlled experiment. It takes place in a real-world setting, rather than under lab conditions. For example, an experiment involving an animal in its natural habitat would be a field experiment.

Variables in an Experiment

Simply put, a variable is anything you can change or control in an experiment. Common examples of variables include temperature, duration of the experiment, composition of a material, amount of light, etc. There are three kinds of variables in an experiment: controlled variables, independent variables and dependent variables .

Controlled variables , sometimes called constant variables are variables that are kept constant or unchanging. For example, if you are doing an experiment measuring the fizz released from different types of soda, you might control the size of the container so that all brands of soda would be in 12-oz cans. If you are performing an experiment on the effect of spraying plants with different chemicals, you would try to maintain the same pressure and maybe the same volume when spraying your plants.

The independent variable is the one factor that you are changing. It is one factor because usually in an experiment you try to change one thing at a time. This makes measurements and interpretation of the data much easier. If you are trying to determine whether heating water allows you to dissolve more sugar in the water then your independent variable is the temperature of the water. This is the variable you are purposely controlling.

The dependent variable is the variable you observe, to see whether it is affected by your independent variable. In the example where you are heating water to see if this affects the amount of sugar you can dissolve , the mass or volume of sugar (whichever you choose to measure) would be your dependent variable.

Examples of Things That Are Not Experiments

• Making a model volcano.
• Making a poster.
• Changing a lot of factors at once, so you can't truly test the effect of the dependent variable.
• Trying something, just to see what happens. On the other hand, making observations or trying something, after making a prediction about what you expect will happen, is a type of experiment.
• Bailey, R.A. (2008). Design of Comparative Experiments . Cambridge: Cambridge University Press. ISBN 9780521683579.
• Beveridge, William I. B., The Art of Scientific Investigation . Heinemann, Melbourne, Australia, 1950.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 0-521-29925-X.
• Hinkelmann, Klaus and Kempthorne, Oscar (2008). Design and Analysis of Experiments, Volume I: Introduction to Experimental Design (Second ed.). Wiley. ISBN 978-0-471-72756-9.
• Shadish, William R.; Cook, Thomas D.; Campbell, Donald T. (2002). Experimental and quasi-experimental designs for generalized causal inference (Nachdr. ed.). Boston: Houghton Mifflin. ISBN 0-395-61556-9.
• 10 Things You Need To Know About Chemistry
• Chemistry 101 - Introduction & Index of Topics
• How to Clean Lab Glassware
• How To Design a Science Fair Experiment
• Understanding Experimental Groups
• What Is a Control Group?
• Examples of Independent and Dependent Variables
• How to Write a Lab Report
• The Difference Between Control Group and Experimental Group
• Scientific Method Lesson Plan
• Pre-Lab Prep for Chemistry Lab
• Difference Between Independent and Dependent Variables
• Which Is Faster: Melting Ice in Water or Air?
• What Is the Difference Between Hard and Soft Science?
• 5 Top Reasons Why Students Fail Chemistry
• What Is a Dependent Variable?

Last updated: 25 September 2024

Next review: 25 September 2025

Examination from April 2021 to February 2024 (adopted 29 February 2024) 

The Council adopted the new Local Plan Part 1 (LP1) on 29 February 2024.

• The Waltham Forest Local Plan Part 1 (LP1) 2020-2035 (PDF) 
• Local Plan Policies Map (February 2024) (PDF) 
• The Adoption Statement (PDF) 
• The Sustainability Appraisal Adoption Statement (PDF) 

The Local Plan Part 1 (LP1) incorporates all the ‘main modifications’ and policy map changes recommended by the Planning Inspectors as necessary to make the Plan sound and/or legally compliant (see below), as well as ‘additional modifications’ that have been made by the Council to realise technical, factual, grammatical and typographical corrections that do not materially affect the policies in the Plan.

• Schedule of Additional Modifications (February 2024) (PDF)

Any person aggrieved by the adoption of the Local Plan Any person aggrieved by the adoption of the Local Plan may make an application to the High Court under Section 113 of the Planning and Compulsory Purchase Act 2004 (as amended).  Any challenge must be made on the grounds that:

a. The document is not within the appropriate power; and/or

b. A procedural requirement has not been complied with.

Any such application must be made promptly, and in any event, no later than the end of the period of six weeks after the date of this notice. The six-week period commences on 29 February 2024 and concludes on 11 April 2024.

Any queries relating to the Local Plan should be made to [email protected] . 

Examination

Before the Council can adopt the Local Plan, it goes through several stages of public consultation. It is also checked to make sure it complies with government policies and regulations. We then submit it to the Secretary of State for independent Examination in Public by the Planning Inspectorate.  

The Waltham Forest Local Plan (Part 1) was submitted to the Secretary of State in April 2021. Examination in Public began with the appointment of the Planning Inspectors, and receipt of their Preliminary Matters in June 2021. Hearing Sessions were held in March 2022 and March 2023. Receipt of the Inspectors' Final Report on 8 January 2024 marked the end of Examination in Public. 

Local Plan Examination Survey  

The Planning Inspectorate would like your feedback about the examination.  If you were involved in the examination because you made comments in writing and/or you took part in a hearing session, then we would be very pleased if you could fill in this short survey. Any comments you make will be confidential.‘ 

Further updates about the progress towards adopting the Local Plan will be posted on this webpage. 

Local Plan Part 1 Towards Adoption

Following the Main Modifications Consultation in September 2023, the Council have now received the Inspectors’ Local Plan Examination Report. 

As requested by the Council, discussed throughout the examination process and consulted on between July and September 2023, the Inspectors’ report recommends a number of “main modifications” to the Waltham Forest Local Plan (LP1) 2020 – 2035. 

The report concludes that, with those Main Modifications incorporated, Waltham Forest Local Plan Part 1 provides an appropriate basis for the planning of the borough, and that it is sound and legally compliant. It also concludes that, subject to those modifications, “the Plan will be viable having regard to policy requirements and the arrangements for Plan monitoring and delivery are robust”. 

The Inspectors' final report and appendix can be found below: 

Waltham Forest LP Final Report – Inspectors Changes 8 January 2024  (PDF) Appendix: Schedule of Main Modifications  (PDF) 

The council has written the attached guide to understand the Inspectors’ report, which you may find useful.

Understanding the Local Plan and Inspectors Report (PDF) 

Arrangements are now being made for the Cabinet and Full Council to consider the adoption of the new Local Plan in light of the Inspectors’ report. 

Local Plan Part 1 Main Modifications Consultation

Consultation on the main modifications finished on Thursday 21 September 2023.

The Council received the following representations on the main modifications.  These have now been sent to the Inspectors for their consideration as they draft the Local Plan Examination Report.

MMC01 – The SoCo  (PDF)

MMC02 – Waltham Forest Civic Society  (PDF)

MMC 03 – M cCarthy and Stone  (PDF)

MMC04 – Conservative Councillors Group  (PDF)

MMC05 – David and Geraldine Kendall  (PDF)

MMC06 – Julian Cheyne  (PDF)

MMC07 – Environment Agency  (PDF)

MMC08 – Mike Sparrow  (PDF)

MMC09 – Prologis c/o Lichfields  (PDF)

MMC10 – Drysdale and District Residents Association (DADRA)   (PDF)

MMC11 – London Hotel Group  (PDF)

MMC12 – BlackRock and NEAT Developments  (PDF)

MMC13 – Waltham Forest Civic Society (Part 2)  (PDF)

MMC14 – Richard Snape  (PDF)

MMC15 – Ruth Lovell  (PDF)

MMC16 – Claire Lovell  (PDF)

MMC17 – Carolyn Lovell  (PDF)

MMC18 – Stonecrest Marble  (PDF)

MMC19 – Tushar Kelkar  (PDF)

MMC20 – Juliet Guiness  (PDF)

MMC21 – Derek Cockerill  (PDF)

MMC22 – Mayor of London  (PDF)

MMC23 – TTL Properties Limited  (PDF)

MMC24 – Nigel Reynolds  (PDF)

MMC25 – Nigel Mear  (PDF)

MMC26 – Janet McPartland  (PDF)

MMC27 – Diane Mackey  (PDF)

MMC28 – Stephen and Sue Malme  (PDF)

MMC29 – Historic England  (PDF)

MMC30 – David Jennings  (PDF)

MMC31 – Adèle Bird  (PDF)

MMC32 – MPC – Designing Out Crime  (PDF)

MMC33 – Barbara Sakarya  (PDF)

MMC34 – Stephen Lovell  (PDF)

MMC35 – Rosy Villar  (PDF)

MMC36 – Ruairidh Villar  (PDF)

MMC37 – Martin Levin  (PDF)

MMC38 – Gerry Delbourgo  (PDF)

MMC39 – Jacqueline Stafford  (PDF)

MMC40 – Delia Born  (PDF)

MMC41 – Sonja Klug  (PDF)

MMC42 – Highams Park Planning Group  (PDF)

MMC43 – Valerie Gay  (PDF)

MMC44 – John Whipp  (PDF)

MMC45 – Shrenee Nesaratnam  (PDF)

MMC46 – June Laverick  (PDF)

MMC47 – Nanette Higgins  (PDF)

MMC48 – N Cope  (PDF)

MMC49 – Ian Rampton  (PDF)

MMC50 – Jarmila Piero  (PDF)

MMC51 – Catherine Skeggs  (PDF)

MMC52 – Michael Killoran  (PDF)

MMC53 – Raymond Moffat  (PDF)

MMC54 – Allan Thompson  (PDF)

MMC55 – Peter Clarke  (PDF)

MMC56 – Natural England  (PDF)

MMC57 – Alan Piper  (PDF)

MMC58 – Loraine Thompson  (PDF)

MMC59 – Michelle Cotter  (PDF)

MMC60 – Gerald Osmund  (PDF)

MMC61 – Chris Thorndyke  (PDF)

MMC62 – Gary Walsh  (PDF)

MMC63 – Margaret Wickenden  (PDF)

MMC64 – Field Family  (PDF)

MMC65 – John Hugill  (PDF)

MMC66 – Elisabeth Flint  (PDF)

MMC67 – Rosemary Langlands  (PDF)

MMC68 – Abigail Woodman  (PDF)

MMC69 – NHS Property Services  (PDF)

MMC70 – Sport England  (PDF)

MMC71 – Rosemary Langlands (Part 2)  (PDF)

MMC72 – Rosemary Langlands (Part 3)  (PDF)

MMC73 – Transport for London  (PDF)

MMC74 – Anthony Thorne  (PDF)

MMC75 – S Clark  (PDF)

Thursday 27 July to Thursday 21 September 2023. 

Following the Examination in Public hearings in March 2023, the Planning Inspectors and the Council have agreed a schedule of Main Modifications proposed to make Local Plan Part 1 sound and/or legally compliant.  

• Local Plan Part 1 Schedule of proposed Main Modifications   (PDF) 

The proposed Main Modifications will now be subject to an eight-week consultation from 27th July to 21st September 2023. Responses to this consultation will be forwarded to the Inspectors, who will take them into account before issuing their report on the Plan. If the Inspectors find the Plan sound, the Council will then be able to take steps to adopt it later in 2023/ early in 2024.  

• Local Plan Part 1 Main Modifications Consultation Letter   (PDF) 
• Local Plan Part 1 Main Modifications Public Notice   (PDF)

The proposed Main Modifications have been subject to updated Sustainability Appraisal and Habitats Regulation Assessment, as set out in the following supporting documents:  

• LPE78 Post Hearing Main Modifications Sustainability Appraisal Report (PDF)
• LPE79 Post Hearing Main Modifications Habitats Regulations Assessment Addendum   (PDF)

The Policies Map illustrates the application of policies in the Plan geographically. It is not defined in legislation as a development plan document, but needs to be updated in line with the proposed Main Modifications. For completeness, the Council is therefore also inviting comments on the Proposed Changed to Submission Policies Map.  

• Proposed Changes to Submission Policies Map   (PDF)

For ease of use, a modified version of the Plan is available below to review alongside the schedule of Main Modifications. It is important to note that this is for information only. Any representations you wish to make should refer to the Main Modifications schedule, and if there are discrepancies between the documents, it is the schedule which takes precedence. 

• Local Plan Part 1 with Proposed Modifications (FOR INFORMATION ONLY)  (PDF)

The Council also proposes a number of “Additional Modifications” to the Plan. These changes are not necessary for legal compliance and/or soundness but are proposed to enhance the clarity of the Plan and provide factual updates. For completeness, a schedule of these Additional Modifications is available below, but please note that representations on Additional Modifications are not sought as part of this consultation. 

• Local Plan Part 1 Schedule of proposed Additional Modifications (FOR INFORMATION ONLY)  (PDF) 

The Council has also made revisions to the following Local Plan evidence documents to inform the proposed Main Modifications: 

• LPE31a Updated Housing Trajectory   (XLSX)
• LPE32a Updated Five Year Housing Land Supply Statement   (PDF)

The Inspectors will take into account any comments received In relation to the following documents which have been published alongside the schedule of Main Modifications:   

• Sustainability Appraisal of the Main Modifications 
• Habitats Regulations Assessment of the Main Modifications 
• Updated Five Year Housing Land Supply Statement  
• Updated Housing Trajectory 

You can make representations on the Main Modifications and/or Policies Map Changes in the following ways:  

• By emailing [email protected]  
• By writing to the Local Plan Team, Place Directorate, Waltham Forest Town Hall, Fellowship Square, Forest Road, London, E17 4JF. 

Please send us your response by 5pm on 21 September 2023 , and include the Main Modification reference number (MM1, MM2 etc) to which your representation refers.  

As the Main Modifications are proposed to make the Plan sound and/or legally compliant, you should consider the tests of soundness when submitting any representation. Paragraph 35 of the National Planning Policy Framework (NPPF 2021) states that plans are sound if they are:  

• positively prepared
• effective and 
• consistent with national policy. 

This consultation is not an opportunity to raise matters relating to other parts of the Plan that have already been considered by the Inspectors during the Examination process. 

Please note that your response will not be treated as confidential. Your comment and name will be made public as it will form part of the Local Plan evidence base, and we are required to provide your full details to the Planning Inspectors and Programme Officer. 

If you have any queries, please email  [email protected]

Local Plan Examination Stage 2 Autumn 2022

Following the March 2023 hearing sessions, the Inspectors have  written their post-hearing letter and the next stage in the Local Plan Examination will be a consultation on proposed main modifications

• Stage 2 Post Hearing Session letter 4.423 (PDF)
• Week 3 follow-up list (PDF) 

The Council has undertaken further work to address the soundness issues highlighted in the Inspectors post hearing letter of 5 May 2022. This updated evidence is detailed below and comprises seven key documents and a Topic Paper which sets out how each issue raised has been addressed.

The Inspectors have now written their Further Matters, Issues and Questions relating to this updated evidence, which will form the basis of a new round of public consultation. The consultation ran from 5 December 2022 to 12 noon on 23 January 2023  with consultation responses directly addressing the questions in the inspectors' Further Matters, Issues and Questions.

Following this consultation, hearing sessions resumed on Tuesday 7 March 2023 with further sessions on 8,9 and 10 of March 2023. These sessions were held at Waltham Forest Town Hall. 

• Draft Stage 2 Hearing Sessions Programme : 7 - 10 March 2023 (PDF) 

Note: You are advised to contact the programme officer if there are any concerns with the draft programme.

• Consultation Letter - Examination in Public Stage 2 Consultation (PDF)
• Inspectors' Further Matters Issues and Questions (PDF)
• Examination Consultation Guidance Note (Amended 09/12/2022)   (PDF)
• Examination Consultation Draft Programme (PDF) 
• Local Plans: taking part in examinations (Link to Government guidance webpage)  

Local Plan Hearing Session Documents and Agendas 

Documents .

LPE67 Stage 2 Hearing Sessions: Council's Opening Statement  (PDF)

LPE68 Amended Table A-1 Existing and Proposed Land Uses (PDF)

LPE69 Proposed modification for Policy 89: Sustainable Design and Construction and 90: Air Pollution (PDF)

LPE70 Proposed modification to Policy 97: Monitoring Growth Targets (PDF)

LPE71 Sustainable Alternative Natural Green Spaces (SANGS) Categories (PDF)

LPE72 Proposed Modification to Policy 83: The Epping Forest and the Epping Forest Special Area of Conservation (PDF)

LPE73 Authority Monitoring Report 2021 to 22 (PDF)

LPE74 Update to LPE74: Updated 5 Year Land Supply (PDF)

LPE75 Proposed modifications to Policy 23: Gypsies and Travellers and Travelling Showpeople (PDF)

LPE76 Proposed modification to Policies 25: Support Economic Growth and Jobs, 26: Safeguarding and Managing Change in Strategic Industrial Land Locations (SIL), 27: Safeguarding and Managing Change in Locally Significant Industrial Sites (LSIS), 28: Safeguarding and Managing Change in Borough Employment Areas (BEA) & 30: Industrial Masterplan Approach (PDF)

LPE77 Proposed Modifications to Policy 93: Managing Flood Risk (PDF)

Hearing Sessions Day 1

Hearing Session Day 1: Matters 1 and 2 (PDF) 

Hearing Sessions Day 2 

Hearing Session Day 2: Matters 3 and 4 (PDF) 

Hearing Sessions Day 3

Matter 5: Suggestion of Modification of Policy 97 (Managing Flood Risk) updated 9.3.23

Matter 6: Avison Young / London Hotel Group Briefing Note 543 Lea Bridge Road 090323

Hearing Session Day 3: Matters 5 and 6 (PDF) 

Responses to Inspectors' Further Matters Issues and Questions

Matter 1: duty to cooperate and other legal requirements .

Council Response

Matter 1: Duty to Cooperate and Other Legal Requirements   (PDF) 

External Responses 

Natural England (PDF)

TFL Property (PDF)

Waltham Forest Civic Society  (PDF)

DADRA (Drysdale and District Residents Association)  (PDF)

R Gillham Chingford Line Users Association / Highams Park Planning Group (PDF)

D Boote  (PDF)

M Chrimes / Costa Coffee Group  (PDF)

M Munday  (PDF)

B O'Leary  (PDF)

S Ritten  (PDF)

A Stannard  (PDF)

A Woodman  (PDF)

Matter 2: Vision, Strategic Objectives, Sustainable Development 

Council Response 

Matter 2: Vision, Strategic Objectives, Sustainable Development (PDF)

External Responses

City of London Corporation  (PDF)

Waltham Forest Conservative Councillors  (PDF)

Waltham Forest Civic Society (PDF)

Highams Park Planning Group  (PDF)

The Arch Company Properties / Turley  (PDF)

Black Rock & Neat Developments / Turley  (PDF)

J Avis  (PDF)

D Boote  (PDF)

R Cade  (PDF)

J Cheyne  (PDF)

H Green  (PDF)

D Matson  (PDF)

J Reades  (PDF)

Matter 3: Housing, Land Supply and Borough-wide Housing Policies 

Matter 3: Housing, Land Supply and Borough-wide Housing Policies   (PDF) 

Aitch Group  (PDF)

Silverwood Properties / Michael Burrows Associates  (PDF)

J Gilbert  (PDF)

J Sterland  (PDF)

Matter 4: Employment and the Vitality of Centres  

Matter 4: Employment and the Vitality of Centres (PDF) 

Greater London Authority (GLA)  (PDF)

Prologis / Lichfields  (PDF)

Matter 5: The Environment, Climate Change, Pollution and Waste Management 

Matter 5: The Environment, Climate Change, Pollution and Waste Management (PDF)

Environment Agency  (PDF)

Transport for London (TfL) Property  (PDF)

Prologis / Knight Frank  (PDF)

A Stannard (PDF)

C Weiss  (PDF)

Matter 6: Built Environment Heritage and Design 

Matter 6: Built Environment Heritage and Design

Greater London Authority (GLA) (PDF)

The London Hotel Group / Avison Young (PDF)

J Cheyne  (PDF)

I McGill (PDF) 

K McGill (PDF)

K Schling  (PDF)

E Turner  (PDF)

C Weiss  (PDF)

Further External Responses

London Parks and Gardens  (PDF) 

Highams Residents Association  (PDF) 

T Buggins  (PDF) 

C De'Ath  (PDF) 

J De'Ath  (PDF) 

S De'Ath  (PDF) 

L Dodd  (PDF) 

B Frearson  (PDF) 

Dr R Gay (PDF)

T Golburn  (PDF) 

J Gilbert (PDF) 

T Gray  (PDF) 

A Harber Kelly  (PDF) 

M Lane  (PDF) 

A Morris  (PDF)

M Munday (PDF) 

M Paul  (PDF) 

G Poulter  (PDF) 

J Poulter  (PDF) 

K Poulter (PDF)  

I Rampton  (PDF) 

Y Sanders  (PDF)

H Shah  (PDF) 

R Shah  (PDF) 

K Sheed  (PDF) 

A Stannard (PDF) 

E Turner  (PDF) 

M Turpin (PDF)

S Wood  (PDF)

Examination Documents 

• LPE30  Examination Stage 2 Topic Paper
• LPE31 Updated Housing Trajectory (XLSX) 
• LPE32  Updated 5 Year Housing Land Supply (PDF) 
• LPE33 Suitable Alternative Natural Greenspace (SANG) Strategy (revised November 2022)  (PDF) 
• LPE34 Flood Risk Sequential Test Statement (PDF) 
• LPE35 Air Quality Study 2 (PDF) 
• LPE36.1 Sustainability Appraisal Report Addendum (PDF) 
• LPE36.2 Sustainability Appraisal Report Addendum - Appendix A  (XLSM) 
• LPE36.3 Sustainability Appraisal Report Addendum - Appendix B   (PDF) 
• LPE36.4 Sustainability Appraisal Report Addendum - Appendix C   (XLSM)
• LPE37.1 Habitats Regulations Assessment (HRA) Report (PDF)  
• LPE37.2 Habitats Regulations Assessment (HRA) Policy Screening (XLXS)  
• LPE38 Statement of General Conformity with the London Plan (New) (PDF)
• LPE39 Statement of Common Ground with the Environment Agency (New) (PDF)
• LPE40 Joint Letter with Natural England (PDF) 
• LPE41 Joint Letter with City of London Corporation (Conservators of Epping Forest) (PDF)
• LPE42 Joint Letter with Lee Valley Regional Park Authority 
• LPE27 Statement of Common Ground with the GLA (Previously Published) 

Borough-wide evidence

• LPE43 The 2019 Epping Forest Visitor Report (PDF) 
• LPE44.1 Growth Capacity Study (2018) (also in the Evidence Base as EB6.2) (PDF) 
• LPE44.2 Growth Capacity Study Full Database (2018) (XLSX)
• LPE45 Character and Intensification Study (also in the Evidence Base EB2.1) (PDF) 
• LPE46.1  Skyline Study November 2021: Introduction, Methodology and North Waltham Forest Sites (PDF) 
• LPE46.2  Skyline Study November 2021: Central Waltham Forest Sites   (PDF) 
• LPE46.3  Skyline Study November 2021: South Waltham Forest Sites 1 (PDF)
• LPE46.4  Skyline Study November 2021: South Waltham Forest Sites 2  (PDF)
• LPE47.1 Executive Summary  (also Key Submission Document KD12.1) (PDF) 
• LPE47.2 Part 1: Introduction and Anticipated Growth to 2035  (also Key Submission Document KD12.1) (PDF) 
• LPE47.3 Part 2: Physical Infrastructure (also Key Submission Document  KD12.3) (PDF) 
• LPE47.4 Part 3: Social and Community Infrastructure  (also Key Submission Document  KD12.4) (PDF) 
• LPE47.5 Part 4: Green and Blue Infrastructure  (also Key Submission Document  KD12.5)  (PDF) 
• LPE47.6 Part 5: Funding, governance and delivery and appendices  (also Key Submission Document KD12.6)  (PDF) 
• LPE47.7 Infrastructure Delivery Schedule  (also Key Submission Document  KD12.7) (PDF) 

Area Specific Evidence

• LPE48 Leyton Leisure Centre Feasibility Study  (PDF)
• LPE49 Leyton Bus Depot Feasibility Study (PDF)
• LPE50 Stanley Road Car Park Feasibility Study (PDF) 
• LPE51 Walthamstow Town Centre Development Framework Brief (PDF)
• LPE52 Leyton Mills Development Framework (PDF)
• LPE53 Blackhorse Lane SIL Masterplan Stage 1 (Baseline Report)  (PDF)
• LPE54.1 Blackhorse Lane SIL Masterplan Stage 2: Part 1 (PDF) 
• LPE54.2 Blackhorse Lane SIL Masterplan Stage 2: Part 2 (PDF) 
• LPE54.3 Blackhorse Lane SIL Masterplan Stage 2: Part 3 (PDF)
• LPE55 Lea Bridge Area Framework (PDF) 
• LPE56 Chingford Mount Town Centre Framework (PDF) 
• LPE57 Leytonstone Town Centre Framework (PDF)
• LPE58 South Leytonstone Area Framework (PDF) 
• LPE59 Forest Road Area Framework (PDF) 

Whipps Cross planning application and supporting evidence 

• LPE60.1 Whipps Cross Air Quality Part 1 (PDF)
• LPE60.2 Whipps Cross Air Quality Part 2   (PDF) 
• LPE60.3 Whipps Cross Air Quality Part 3   (PDF) 
• LPE61 Whipps Cross Planning Application: ES non-technical Summary (PDF) 
• LPE62 Whipps Cross Planning Application: Summary of Mitigation Measures and Residual Effects   (PDF) 
• LPE63 Whipps Cross Planning Application: Minutes of meeting with Natural England (PDF) 

New Statement of Common Ground with Natural England

• LPE64 New Statement of Common Ground with Natural England

Website Links 

External 

• The Conservation of Habitats and the Species Regulations (2017) 

Waltham Forest 

• Waltham Forest: Local Plan (Submission to Planning Inspectorate)  
• Waltham Forest: Local Plan Evidence Base  
• Waltham Forest: Lea Bridge Area Framework  
• Waltham Forest: Improvements to Markhouse Corner  
• Waltham Forest: Leytonstone Town Centre Framework  
• Waltham Forest: Chingford Mount Town Centre Framework  
• Waltham Forest: South Leytonstone Area Framework  
• Waltham Forest: Forest Road Corridor Area Framework  
• Waltham Forest: Leyton Mills  
• Waltham Forest: Blackhorse Lane Masterplan  

Correspondence between Council and planning inspectors

1 December 2022

Council Response 1 December 2022 (PDF)

19 October 2022

Council response 19 October 2022 (PDF)

11 October 2022

Letter from the Inspectors to the Council 11 October 2022 (PDF)

29 September 2022

Submission Letter from the Council to the Inspectors 29 September 2022 (PDF)

06 September 2022 

August update letter to the Inspectors, 06 September 2022  (PDF)

Work programme update August 2022  (PDF)

29 July 2022

Update letter to the Inspectors, 29 July 2022 (PDF) 

Work programme update July 2022 (PDF) 

30 June 2022

Update letter to the Inspectors, 30 June 2022  (PDF)

Work programme update June 2022  (PDF)

27 May 2022

Letter from the Inspectors to the Council 27 May 2022  (PDF)

Council response 31 May 2022 (PDF) 

Provisional Stage 2 Work Programme (PDF) 

Local Plan post hearings letter and council response

On 5 May 2022 and as a formal part of the examination process, the Council received a post hearing letter from the Planning Inspectors setting out their initial findings and options for the progress of Local Plan part 1. The Council has submitted a written response to this letter on 11 May 2022. Copies of both letters are available below: 

LP1 Post Hearings letter 5 May 2022  (PDF)

Council response to Post Hearings Letter  (PDF) 

Local Plan post hearing sessions follow-up lists 

Week 2 Follow up list  (PDF)

Week 1 Follow up list  (PDF)

Local Plan hearing sessions broadcasting and recording

Week 2 Hearing sessions 

LPE19 Provisional hearings programme V6  (PDF)

Local Plan hearing sessions day 6 matter 7 and matter 8, Thursday 24 March 2022

9:30am Matter 7: 

Hearing session recording, part 1

Hearing session recording, part 2 

2:00pm Matter 8: 

4:15pm Round-up session: 

Round-up session recording, part 1

Local Plan hearing sessions day 5 matter 6 and matter 4 continued. Live broadcast sessions and recordings Wednesday 23 March 2022

9:30am Matter 6 : 

Hearing session recording, part 2

LPE28 Email from D. Matson 23.03.2022  (PDF)

Local Plan hearing sessions day 4, matters 4 and 5 recordings, Tuesday 22 March 2022 

2:00pm Matter 4 continued: 

Hearing session recording, part 3

Hearing session recording, part 4

9:30am Matter 4:  

LPE27  Statement of common ground with the Greater London Authority (GLA)  (PDF) 

2:00pm Matter 5:  

• LPE26 Proposed modifications to Policy 83 for matter 5 hearing session  (PDF)

LPE28  Suggestion for modification of Policy 97 (Flood Risk) Dr RJ Gay on behalf of the Waltham Forest Civic Society.  (PDF) 

Week 1 Hearing sessions

Local Plan hearing sessions day 3, matter 3 recordings, Thursday 17 March 2022

Hearing session recording, part 3 

Local Plan hearing sessions day 2, matter 2 recordings, Wednesday 16 March 2022

Local Plan hearing sessions day 1, matter 1 recordings, Tuesday 16 March 2022 

Local Plan examination documents (LP1)

• Local Plan examination documents index  (PDF)
• Procedure guide for Local Plan examinations
• LPE0 Inspectors preliminary matters - June 2021  (PDF)
• LPE1 Natural England response to the updated HRA: 16 July 2021  (PDF)
• LPE2 Matter 1 Dtc addendum  (PDF)
• LPE3 Matter 2 statements of common ground  (PDF)
• LPE4 Matter 3 HRA topic paper  (PDF)
• LPE5 Matter 4 modifications  (PDF)
• LPE6 Matter 6 green belt  (PDF)
• LPE7 Matter 7 general matters  (PDF)
• LPE8 Matter 8 Waltham Forest employment land audit - April 2021  (PDF)
• LPE9 Housing position statement September 2021  (PDF)
• LPE10 Housing trajectory summary  (PDF)
• LPE11 Transport topic paper  (PDF)
• LPE12 Cultural infrastructure study  (PDF)
• LPE13 Examination guidance note  (PDF)
• LPE14 Matters issues and questions  (PDF)
• LPE15 Provisional hearings programme   (PDF)
• LPE17 LP1 Consultation report addendum  (PDF)
• LPE18 Virtual hearing participation guidance note (PDF)
• LPE19 Provisional hearings programme V6   (PDF)
• LPE20 London Legacy Development Corporation (LLDC) Local Plan 2020 to 2036 
• LPE21 North London Waste Plan (NLWP) (adopted March 2022)  (PDF)
• LPE22.1 The Highams Park Neighbourhood Plan (May 2020)  (PDF)
• LPE22.2 The Highams Park Plan annex 1, aspirations, projects and actions. 
• LPE23.1 Habitats and Regulations Assessment (HRA) (PDF)
• LPE23.2 Habitats and Regulations Assessment addendum 1 (HRA) (PDF) 
• LPE23.3 Draft Habitats Regulations Assessment Air Quality Mitigation Strategy (AQMS) (PDF)
• LPE23.4 Draft Strategy to provide Suitable Alternative Natural Green Space (SANGS) (PDF)
• LPE24 Authority monitoring report 2020 / 2021 (PDF)  
• LPE25 Documents to support the implementation of the Local Plan  (PDF)
• LPE27 Statement of common ground with the Greater London Authority (GLA)  (PDF)
• LPE28  Suggestion for modification of Policy 97 (Flood Risk) Dr RJ Gay on behalf of the Waltham Forest Civic Society.
• LPE28 Email from D. Matson 23.03.2022 
• LPE65 Joint Nature and Conservation Committee (JNCC) Guidance on Decision-making Thresholds for Air Pollution Chapman, C. and Kite, B. December 2021 (PDF)
• LPE66 2017 Wealden Judgement between Wealden District Council - and - (1) Secretary of State for Communities and Local Government, (2) Lewes District Council (3) South Downs National Park Authority - and - Natural England. (PDF) 

Local Plan matters issues and questions

• MIQ1 Response to matter 1

Agenda matter 1

• MIQ2 Response to matter 2

Agenda matter 2

• MIQ3 Response to matter 3

Agenda matter 3

• MIQ4 Response to matter 4

Agenda matter 4

• MIQ5 Response to matter 5 amended 08.03

Agenda matter 5

Proposed modifications to Policy 83 for matter 5 hearing session

• MIQ6 Response to matter 6 amended 14.03

Agenda matter 6

• MIQ7 Response to matter 7

Agenda matter 7

• MIQ8 Response to matter 8

Agenda matter 8

• MIQ9 Response to additional question 188

Local Plan hearing statements

• Natural England
• City of London Conservators of Epping Forest
• Thames Water
• Greater London Authority
• Highams Park Neighbourhood Planning Group
• Mayors Letter - to be read with responses from Highams Park Neighbourhood Planning Group and G Reeve
• Dr R Gay: Waltham Forest Civic Society
• D Matson  
• B O'Leary - Submission 1  
• B O'Leary - Submission 2
• B O'Leary - Submission 3  
• B O'Leary - Submission 4
• Rolfe Judd - Bywaters
• BNP Paribas - LocatED - Matter 2 spatial strategy
• BNP Paribas - LocatED - Matter 2 housing supply

Local Plan Submission to Planning Inspectorate.

The Council submitted Local Plan Part 1 to the Secretary of State on 30 April 2021. The Planning Inspectorate appointed Sarah Housden and Catherine Jack as joint Planning Inspectors. They will carried out the independent examination on the Local Plan (LP1).

Submission notice  (PDF)

Submission letter  (PDF)

Key Submission documents 

KD0:  Submission documents  (PDF)

KD1:  Waltham Forest Local Plan (Shaping the borough, LP1) 2020-2035 - Proposed submission document, October 2020  (PDF)

KD2:  Schedule of proposed changes to the published plan, April 2021  (PDF)

KD3:  Local Plan policies map  (PDF)

KD4: Waltham Forest Local Plan (LP1) - Sustainability Appraisal (Submission Version) April 2021 

• KD4.1:  Sustainability appraisal Non-Technical-Summary (NTS)  (PDF)
• KD4.2:  Sustainability appraisal report  (PDF)
• KD4.3:  Appendix A  (PDF)
• KD4.4:  Appendix B  (PDF)
• KD4.5:  Appendix C  (PDF)
• KD4.6:  Appendix D  (PDF)
• KD4.7:  Appendix E  (PDF)

KD5: Waltham Forest Local Plan (LP1) - Habitats Regulation Assessment (Submission version), April 2021 

• KD5.1;:  Waltham Forest Local Plan (LP1) - Habitats Regulation Assessment (Submission version), April 2021  (PDF)
• KD5.2:  Waltham Forest Local Plan (LP1) - Detailed Screening of Local Plan Policies  (Excel)

KD6: Consultation Statement

• KD6.1:  Consultation statement (regulation 22)  (PDF)
• KD6.2:  Copies of representations made under regulation 20 updated  (PDF)

KD7:  Duty to cooperate statement April 2021  (PDF)

KD8: Schedule of Representations Made (Regulation 19 Stage)  

• KD8.1:  Schedule representation in plan order  (Excel)
• KD8.2:  Schedule of representations in respondent name order  (PDF)
• KD8.3:  LP1 Consultation report addendum  (Word)

KD9:  Equalities impact assessment  (PDF)

KD10:  Waltham Forest Local development scheme 2020 to 2023  (PDF)

KD11:  Waltham Forest statement of community involvement 2018  (PDF)

KD11.1:  Waltham Forest statement of community involvement with addendum  (PDF)

KD12: Infrastructure Delivery Plan, Autumn 2021 

• KD12.1:  Executive summary  (PDF)
• KD12.2:  Part 1: Introduction and anticipated growth to 2035  (PDF)
• KD12.3:  Part 2: Physical infrastructure  (PDF)
• KD12.4:  Part 3: Social infrastructure  (PDF)
• KD12.5:  Part 4: Green and blue infrastructure  (PDF)
• KD12.6:  Part 5: Funding, governance and delivery and appendices  (PDF)
• KD12.7: Infrastructure Delivery Schedule

KD13: Whole Plan Viability Study, April 2021

• KD13.1:  London Borough of Waltham Forest Part 1 Local Plan 2020-2025 [LP1] viability study  (PDF)

Supporting documents 

SD1:  Shaping the Borough - Waltham Forest Local Plan, Draft Site Allocations Document (LP2), September 2020  (PDF)

SD2:  Schedule of Changes made to the Waltham Forest Draft Local Plan - Shaping the Borough (included in the Proposed Submission Local Plan)  (PDF)

SD3: Shaping the Borough Draft Local Plan (Reg 18) 2020 to 2025

• SD3.1:  Draft Local Plan (Reg 18)  (PDF) - Waltham Forest Local Plan (Shaping the Borough, Draft Plan), July 2019 
• SD3.2:  Draft Local Plan Appendices (Reg 18)  (PDF)

SD4:  Waltham Forest Local Plan (Shaping the Borough Draft Plan Consultation Report June 2020  (PDF)

SD5: Sustainability Appraisal Report – Draft Local Plan, July 2019 

• SD5.1  Draft Local Plan Regulation 18 Sustainability Appraisal LP1 (2019)  (PDF)
• SD5.2:  Reg 18 Sustainability Appraisal LP1 Reg 18 Non-Technical Summary  (PDF)
• SD5.3:  Appendix A Baseline Data Reg 18  (PDF)
• SD5.4:  Appendix B Review of Relevant Plans, Policies and Programmes Reg 18  (PDF)
• SD5.5:  Appendix C Spatial Strategy Policies Assessment Matrix Reg 18  (Excel)
• SD5.6: Appendix D Local Plan Policies Thematic Policies Assessment Reg 18  (Excel)
• SD5.7:  Appendix E Spatial Strategy Options Assessment Summary Reg 18  (PDF)
• SD5.8:  Appendix F Direction of Travel Options Assessment 2018  (PDF)

SD6:  Waltham Forest Local Plan (Direction of Travel Document, Regulation 18), November 2017  (PDF)

SD7:  Waltham Forest Local Plan (Direction of Travel Document, Regulation 18), Consultation Report  (PDF)

SD8:  Sustainability Appraisal Report (Direction of Travel Document) November 2017  (PDF)

Other documents  

The Local Plan is supported by a range of  evidence based documents .