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Quantitative Research – Methods, Types and Analysis
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Quantitative Research
Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions . This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected. It often involves the use of surveys, experiments, or other structured data collection methods to gather quantitative data.
Quantitative Research Methods
Quantitative Research Methods are as follows:
Descriptive Research Design
Descriptive research design is used to describe the characteristics of a population or phenomenon being studied. This research method is used to answer the questions of what, where, when, and how. Descriptive research designs use a variety of methods such as observation, case studies, and surveys to collect data. The data is then analyzed using statistical tools to identify patterns and relationships.
Correlational Research Design
Correlational research design is used to investigate the relationship between two or more variables. Researchers use correlational research to determine whether a relationship exists between variables and to what extent they are related. This research method involves collecting data from a sample and analyzing it using statistical tools such as correlation coefficients.
Quasi-experimental Research Design
Quasi-experimental research design is used to investigate cause-and-effect relationships between variables. This research method is similar to experimental research design, but it lacks full control over the independent variable. Researchers use quasi-experimental research designs when it is not feasible or ethical to manipulate the independent variable.
Experimental Research Design
Experimental research design is used to investigate cause-and-effect relationships between variables. This research method involves manipulating the independent variable and observing the effects on the dependent variable. Researchers use experimental research designs to test hypotheses and establish cause-and-effect relationships.
Survey Research
Survey research involves collecting data from a sample of individuals using a standardized questionnaire. This research method is used to gather information on attitudes, beliefs, and behaviors of individuals. Researchers use survey research to collect data quickly and efficiently from a large sample size. Survey research can be conducted through various methods such as online, phone, mail, or in-person interviews.
Quantitative Research Analysis Methods
Here are some commonly used quantitative research analysis methods:
Statistical Analysis
Statistical analysis is the most common quantitative research analysis method. It involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis can be used to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
Regression Analysis
Regression analysis is a statistical technique used to analyze the relationship between one dependent variable and one or more independent variables. Researchers use regression analysis to identify and quantify the impact of independent variables on the dependent variable.
Factor Analysis
Factor analysis is a statistical technique used to identify underlying factors that explain the correlations among a set of variables. Researchers use factor analysis to reduce a large number of variables to a smaller set of factors that capture the most important information.
Structural Equation Modeling
Structural equation modeling is a statistical technique used to test complex relationships between variables. It involves specifying a model that includes both observed and unobserved variables, and then using statistical methods to test the fit of the model to the data.
Time Series Analysis
Time series analysis is a statistical technique used to analyze data that is collected over time. It involves identifying patterns and trends in the data, as well as any seasonal or cyclical variations.
Multilevel Modeling
Multilevel modeling is a statistical technique used to analyze data that is nested within multiple levels. For example, researchers might use multilevel modeling to analyze data that is collected from individuals who are nested within groups, such as students nested within schools.
Applications of Quantitative Research
Quantitative research has many applications across a wide range of fields. Here are some common examples:
- Market Research : Quantitative research is used extensively in market research to understand consumer behavior, preferences, and trends. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform marketing strategies, product development, and pricing decisions.
- Health Research: Quantitative research is used in health research to study the effectiveness of medical treatments, identify risk factors for diseases, and track health outcomes over time. Researchers use statistical methods to analyze data from clinical trials, surveys, and other sources to inform medical practice and policy.
- Social Science Research: Quantitative research is used in social science research to study human behavior, attitudes, and social structures. Researchers use surveys, experiments, and other quantitative methods to collect data that can inform social policies, educational programs, and community interventions.
- Education Research: Quantitative research is used in education research to study the effectiveness of teaching methods, assess student learning outcomes, and identify factors that influence student success. Researchers use experimental and quasi-experimental designs, as well as surveys and other quantitative methods, to collect and analyze data.
- Environmental Research: Quantitative research is used in environmental research to study the impact of human activities on the environment, assess the effectiveness of conservation strategies, and identify ways to reduce environmental risks. Researchers use statistical methods to analyze data from field studies, experiments, and other sources.
Characteristics of Quantitative Research
Here are some key characteristics of quantitative research:
- Numerical data : Quantitative research involves collecting numerical data through standardized methods such as surveys, experiments, and observational studies. This data is analyzed using statistical methods to identify patterns and relationships.
- Large sample size: Quantitative research often involves collecting data from a large sample of individuals or groups in order to increase the reliability and generalizability of the findings.
- Objective approach: Quantitative research aims to be objective and impartial in its approach, focusing on the collection and analysis of data rather than personal beliefs, opinions, or experiences.
- Control over variables: Quantitative research often involves manipulating variables to test hypotheses and establish cause-and-effect relationships. Researchers aim to control for extraneous variables that may impact the results.
- Replicable : Quantitative research aims to be replicable, meaning that other researchers should be able to conduct similar studies and obtain similar results using the same methods.
- Statistical analysis: Quantitative research involves using statistical tools and techniques to analyze the numerical data collected during the research process. Statistical analysis allows researchers to identify patterns, trends, and relationships between variables, and to test hypotheses and theories.
- Generalizability: Quantitative research aims to produce findings that can be generalized to larger populations beyond the specific sample studied. This is achieved through the use of random sampling methods and statistical inference.
Examples of Quantitative Research
Here are some examples of quantitative research in different fields:
- Market Research: A company conducts a survey of 1000 consumers to determine their brand awareness and preferences. The data is analyzed using statistical methods to identify trends and patterns that can inform marketing strategies.
- Health Research : A researcher conducts a randomized controlled trial to test the effectiveness of a new drug for treating a particular medical condition. The study involves collecting data from a large sample of patients and analyzing the results using statistical methods.
- Social Science Research : A sociologist conducts a survey of 500 people to study attitudes toward immigration in a particular country. The data is analyzed using statistical methods to identify factors that influence these attitudes.
- Education Research: A researcher conducts an experiment to compare the effectiveness of two different teaching methods for improving student learning outcomes. The study involves randomly assigning students to different groups and collecting data on their performance on standardized tests.
- Environmental Research : A team of researchers conduct a study to investigate the impact of climate change on the distribution and abundance of a particular species of plant or animal. The study involves collecting data on environmental factors and population sizes over time and analyzing the results using statistical methods.
- Psychology : A researcher conducts a survey of 500 college students to investigate the relationship between social media use and mental health. The data is analyzed using statistical methods to identify correlations and potential causal relationships.
- Political Science: A team of researchers conducts a study to investigate voter behavior during an election. They use survey methods to collect data on voting patterns, demographics, and political attitudes, and analyze the results using statistical methods.
How to Conduct Quantitative Research
Here is a general overview of how to conduct quantitative research:
- Develop a research question: The first step in conducting quantitative research is to develop a clear and specific research question. This question should be based on a gap in existing knowledge, and should be answerable using quantitative methods.
- Develop a research design: Once you have a research question, you will need to develop a research design. This involves deciding on the appropriate methods to collect data, such as surveys, experiments, or observational studies. You will also need to determine the appropriate sample size, data collection instruments, and data analysis techniques.
- Collect data: The next step is to collect data. This may involve administering surveys or questionnaires, conducting experiments, or gathering data from existing sources. It is important to use standardized methods to ensure that the data is reliable and valid.
- Analyze data : Once the data has been collected, it is time to analyze it. This involves using statistical methods to identify patterns, trends, and relationships between variables. Common statistical techniques include correlation analysis, regression analysis, and hypothesis testing.
- Interpret results: After analyzing the data, you will need to interpret the results. This involves identifying the key findings, determining their significance, and drawing conclusions based on the data.
- Communicate findings: Finally, you will need to communicate your findings. This may involve writing a research report, presenting at a conference, or publishing in a peer-reviewed journal. It is important to clearly communicate the research question, methods, results, and conclusions to ensure that others can understand and replicate your research.
When to use Quantitative Research
Here are some situations when quantitative research can be appropriate:
- To test a hypothesis: Quantitative research is often used to test a hypothesis or a theory. It involves collecting numerical data and using statistical analysis to determine if the data supports or refutes the hypothesis.
- To generalize findings: If you want to generalize the findings of your study to a larger population, quantitative research can be useful. This is because it allows you to collect numerical data from a representative sample of the population and use statistical analysis to make inferences about the population as a whole.
- To measure relationships between variables: If you want to measure the relationship between two or more variables, such as the relationship between age and income, or between education level and job satisfaction, quantitative research can be useful. It allows you to collect numerical data on both variables and use statistical analysis to determine the strength and direction of the relationship.
- To identify patterns or trends: Quantitative research can be useful for identifying patterns or trends in data. For example, you can use quantitative research to identify trends in consumer behavior or to identify patterns in stock market data.
- To quantify attitudes or opinions : If you want to measure attitudes or opinions on a particular topic, quantitative research can be useful. It allows you to collect numerical data using surveys or questionnaires and analyze the data using statistical methods to determine the prevalence of certain attitudes or opinions.
Purpose of Quantitative Research
The purpose of quantitative research is to systematically investigate and measure the relationships between variables or phenomena using numerical data and statistical analysis. The main objectives of quantitative research include:
- Description : To provide a detailed and accurate description of a particular phenomenon or population.
- Explanation : To explain the reasons for the occurrence of a particular phenomenon, such as identifying the factors that influence a behavior or attitude.
- Prediction : To predict future trends or behaviors based on past patterns and relationships between variables.
- Control : To identify the best strategies for controlling or influencing a particular outcome or behavior.
Quantitative research is used in many different fields, including social sciences, business, engineering, and health sciences. It can be used to investigate a wide range of phenomena, from human behavior and attitudes to physical and biological processes. The purpose of quantitative research is to provide reliable and valid data that can be used to inform decision-making and improve understanding of the world around us.
Advantages of Quantitative Research
There are several advantages of quantitative research, including:
- Objectivity : Quantitative research is based on objective data and statistical analysis, which reduces the potential for bias or subjectivity in the research process.
- Reproducibility : Because quantitative research involves standardized methods and measurements, it is more likely to be reproducible and reliable.
- Generalizability : Quantitative research allows for generalizations to be made about a population based on a representative sample, which can inform decision-making and policy development.
- Precision : Quantitative research allows for precise measurement and analysis of data, which can provide a more accurate understanding of phenomena and relationships between variables.
- Efficiency : Quantitative research can be conducted relatively quickly and efficiently, especially when compared to qualitative research, which may involve lengthy data collection and analysis.
- Large sample sizes : Quantitative research can accommodate large sample sizes, which can increase the representativeness and generalizability of the results.
Limitations of Quantitative Research
There are several limitations of quantitative research, including:
- Limited understanding of context: Quantitative research typically focuses on numerical data and statistical analysis, which may not provide a comprehensive understanding of the context or underlying factors that influence a phenomenon.
- Simplification of complex phenomena: Quantitative research often involves simplifying complex phenomena into measurable variables, which may not capture the full complexity of the phenomenon being studied.
- Potential for researcher bias: Although quantitative research aims to be objective, there is still the potential for researcher bias in areas such as sampling, data collection, and data analysis.
- Limited ability to explore new ideas: Quantitative research is often based on pre-determined research questions and hypotheses, which may limit the ability to explore new ideas or unexpected findings.
- Limited ability to capture subjective experiences : Quantitative research is typically focused on objective data and may not capture the subjective experiences of individuals or groups being studied.
- Ethical concerns : Quantitative research may raise ethical concerns, such as invasion of privacy or the potential for harm to participants.
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- What Is Quantitative Research? | Definition & Methods
What Is Quantitative Research? | Definition & Methods
Published on 4 April 2022 by Pritha Bhandari . Revised on 10 October 2022.
Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.
Quantitative research is the opposite of qualitative research , which involves collecting and analysing non-numerical data (e.g. text, video, or audio).
Quantitative research is widely used in the natural and social sciences: biology, chemistry, psychology, economics, sociology, marketing, etc.
- What is the demographic makeup of Singapore in 2020?
- How has the average temperature changed globally over the last century?
- Does environmental pollution affect the prevalence of honey bees?
- Does working from home increase productivity for people with long commutes?
Table of contents
Quantitative research methods, quantitative data analysis, advantages of quantitative research, disadvantages of quantitative research, frequently asked questions about quantitative research.
You can use quantitative research methods for descriptive, correlational or experimental research.
- In descriptive research , you simply seek an overall summary of your study variables.
- In correlational research , you investigate relationships between your study variables.
- In experimental research , you systematically examine whether there is a cause-and-effect relationship between variables.
Correlational and experimental research can both be used to formally test hypotheses , or predictions, using statistics. The results may be generalised to broader populations based on the sampling method used.
To collect quantitative data, you will often need to use operational definitions that translate abstract concepts (e.g., mood) into observable and quantifiable measures (e.g., self-ratings of feelings and energy levels).
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Once data is collected, you may need to process it before it can be analysed. For example, survey and test data may need to be transformed from words to numbers. Then, you can use statistical analysis to answer your research questions .
Descriptive statistics will give you a summary of your data and include measures of averages and variability. You can also use graphs, scatter plots and frequency tables to visualise your data and check for any trends or outliers.
Using inferential statistics , you can make predictions or generalisations based on your data. You can test your hypothesis or use your sample data to estimate the population parameter .
You can also assess the reliability and validity of your data collection methods to indicate how consistently and accurately your methods actually measured what you wanted them to.
Quantitative research is often used to standardise data collection and generalise findings . Strengths of this approach include:
- Replication
Repeating the study is possible because of standardised data collection protocols and tangible definitions of abstract concepts.
- Direct comparisons of results
The study can be reproduced in other cultural settings, times or with different groups of participants. Results can be compared statistically.
- Large samples
Data from large samples can be processed and analysed using reliable and consistent procedures through quantitative data analysis.
- Hypothesis testing
Using formalised and established hypothesis testing procedures means that you have to carefully consider and report your research variables, predictions, data collection and testing methods before coming to a conclusion.
Despite the benefits of quantitative research, it is sometimes inadequate in explaining complex research topics. Its limitations include:
- Superficiality
Using precise and restrictive operational definitions may inadequately represent complex concepts. For example, the concept of mood may be represented with just a number in quantitative research, but explained with elaboration in qualitative research.
- Narrow focus
Predetermined variables and measurement procedures can mean that you ignore other relevant observations.
- Structural bias
Despite standardised procedures, structural biases can still affect quantitative research. Missing data , imprecise measurements or inappropriate sampling methods are biases that can lead to the wrong conclusions.
- Lack of context
Quantitative research often uses unnatural settings like laboratories or fails to consider historical and cultural contexts that may affect data collection and results.
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.
In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.
Operationalisation means turning abstract conceptual ideas into measurable observations.
For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.
Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.
Reliability and validity are both about how well a method measures something:
- Reliability refers to the consistency of a measure (whether the results can be reproduced under the same conditions).
- Validity refers to the accuracy of a measure (whether the results really do represent what they are supposed to measure).
If you are doing experimental research , you also have to consider the internal and external validity of your experiment.
Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.
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What is Quantitative Research: Its Definition, Methods & Examples
In the realm of research methodologies, quantitative research and analytics shines as a robust and systematic approach to collecting, analyzing, and interpreting numerical data. It provides a framework for measuring variables, conducting statistical analyses, and drawing objective conclusions. Whether you are a student embarking on a research project or a professional seeking to expand your knowledge, understanding the essence of quantitative research is vital.
By the end of this comprehensive guide, you will gain a profound understanding of quantitative research and its immense value in generating actionable insights for decision-making with the help of big market research firms .
So, let’s get started with the basics of quantitative research and analytics
What is quantitative research?
Quantitative research is a systematic and structured approach to gathering, analyzing, and interpreting numerical data in order to understand and explain phenomena. It involves the collection of objective, measurable data that can be quantified and analyzed using statistical methods. This research method is focused on obtaining precise and reliable information to uncover patterns, relationships, and trends within the data.
In quantitative research, variables are identified and measured, often through the use of surveys, experiments, or other data collection techniques. These variables can be numeric in nature, such as age, income, or ratings, allowing for statistical analysis and mathematical manipulation. The data collected is then analyzed using statistical techniques to identify patterns, associations, and correlations.
The main objective of quantitative research is to generalize findings from a sample to a larger population. This is achieved through the use of representative sampling techniques and statistical inference. By employing statistical analysis, researchers can draw conclusions, make predictions, and test hypotheses based on the data collected.
Quantitative research is characterized by its emphasis on objectivity, precision, and replicability. It provides a structured framework that allows for the systematic collection and analysis of data, ensuring rigor and reliability in the research process. Additionally, quantitative research enables researchers to make comparisons, establish cause-and-effect relationships, and identify trends over time.
Methods of Quantitative Research
Many of the big market research companies employ various methods of conducting research that provide insights on the customer behavior. Here are some of the most common ones.
Surveys are a prevalent quantitative research method that involves structured questionnaires administered to a sample of respondents. Through surveys , researchers can gather numerical data on a wide range of topics, such as demographics, opinions, preferences, or behaviors. Statistical analysis is then applied to extract meaningful insights from the collected data.
Experiments
Experiments are controlled studies designed to investigate cause-and-effect relationships. Researchers manipulate variables within a controlled environment and observe their impact on the outcome. By carefully designing and executing experiments, researchers can draw statistically valid conclusions and establish causal relationships.
Observational Studies
Observational studies involve systematically observing and recording behaviors, actions, or events without interfering or manipulating variables. Researchers collect quantitative data through direct observation, often using standardized protocols. This method is commonly used in fields such as psychology, sociology, and anthropology.
Primary Quantitative Research
Primary quantitative research refers to the collection and analysis of new numerical data to address a specific research question or hypothesis. It involves designing and implementing a study from scratch, rather than relying on existing data or secondary sources. Primary quantitative research typically follows a structured and systematic approach to ensure the collection of reliable and valid data.
To conduct primary quantitative research, researchers often use various methods such as surveys, experiments, or observations to gather numerical data from a sample or population. They then employ statistical analysis techniques to analyze the data and draw objective conclusions
Secondary quantitative data analysis
Secondary data analysis involves using existing data sources to answer research questions. Researchers analyze pre-existing datasets, such as government statistics, industry reports, or previously conducted surveys. This method allows researchers to leverage existing data without the need for new data collection.
Examples of Quantitative Research
Market research.
Quantitative research is extensively utilized in market research to gain insights into consumer behavior, preferences, and market trends. Surveys are commonly employed to collect data on buying habits, brand awareness, customer satisfaction, and market segmentation. Statistical analysis techniques enable researchers to identify target markets, predict demand, and inform marketing strategies.
Health Studies
Quantitative research methods play a vital role in health studies, including epidemiology, clinical trials, and public health research . Large-scale surveys, controlled experiments, and statistical modeling are employed to collect and analyze data on disease prevalence, treatment outcomes, patient satisfaction, and health behavior patterns. These insights contribute to evidence-based healthcare decision-making.
Educational Research
In the realm of education, quantitative research is instrumental in evaluating teaching methods, measuring student learning outcomes, and assessing the effectiveness of educational interventions. Surveys, tests, and experiments are conducted to gather data on factors such as academic performance, student engagement, and the impact of instructional techniques. Statistical analysis enables researchers to draw conclusions and inform educational policies and practices.
Social Sciences
Quantitative research is prevalent in various social science disciplines, including sociology, psychology, and economics. Researchers employ quantitative methods to study social phenomena, attitudes, behaviors, and economic trends. Surveys, experiments, and statistical models allow for the examination of large datasets and the identification of patterns, correlations, and trends within social systems.
Partner with the Best quantitative market research services Provider
Quantitative research serves as a powerful tool for generating numerical data, providing valuable insights, and informing evidence-based decision-making. By employing methods such as surveys, experiments, observational studies, and secondary data analysis, researchers can uncover patterns, relationships, and trends within the data. The applications of quantitative research are vast, spanning market research, health studies, education, and social sciences. Armed with a comprehensive understanding of this methodology, researchers and decision-makers can harness the power of quantitative research to make informed choices and drive success.
Insights Opinion offers accurate quantitative research solutions to make your business stand out among competitors. Our team of research experts cautiously reviews all the intricacies of the data to ensure exceptionally high-quality data reports. While working with us, you will get application of offline and online methodologies including CATI (Computer Aided Telephonic Interview), CAWI (Computer Aided Web interview), PAPI (Pen and Paper Interview). And CLT (Central Location Test). Along with the insightful dashboards, our team is also qualified to generate customized reports within strict deadlines making your reporting easier, efficient and time-bound.
Get in touch with us today to get the benefits of quantitative research and analytics.
Q 1. Can quantitative research be used in all the business verticals?
Yes, quantitative research can be applied anywhere to gain better understanding of the customers.
Q 2. Are there any limitations or criticisms of quantitative research?
Like any research method, quantitative research has its limitations. It is important to consider the research question and the context to determine if quantitative research is the most appropriate approach.
Q 3. Are there any ethical considerations specific to quantitative research?
Ethical considerations in quantitative research are similar to other types of research. However, experienced researchers through any big market research company ensure the confidentiality and privacy of participants when handling large datasets.
Q 4. Is quantitative research suitable for studying rare or unique events?
Quantitative research is generally more suitable for studying phenomena that are common or occur frequently.
Q 5. How can qualitative and quantitative research methods complement each other?
Qualitative and quantitative research methods can be complementary. While quantitative research focuses on numerical data and statistical analysis, qualitative research emphasizes subjective experiences, meanings, and in-depth understanding. By combining both methods, researchers can gain a comprehensive understanding of a phenomenon, using qualitative data to explore underlying reasons and quantitative data to identify patterns and trends.
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Quantitative Research
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Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data. Descartes, the seventeenth-century philosopher, suggested that how the results are achieved is often more important than the results themselves, as the journey taken along the research path is a journey of discovery. High-quality quantitative research is characterized by the attention given to the methods and the reliability of the tools used to collect the data. The ability to critique research in a systematic way is an essential component of a health professional’s role in order to deliver high quality, evidence-based healthcare. This chapter is intended to provide a simple overview of the way new researchers and health practitioners can understand and employ quantitative methods. The chapter offers practical, realistic guidance in a learner-friendly way and uses a logical sequence to understand the process of hypothesis development, study design, data collection and handling, and finally data analysis and interpretation.
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Quantitative research is the process of collecting and analyzing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalize results to wider populations.
Against this backdrop, this guide offers an overview of quantitative research, elucidating its core motivations, defining characteristics, and methodological considerations.
Quantitative research is a type of research that collects and analyzes numerical data to test hypotheses and answer research questions. This research typically involves a large sample size and uses statistical analysis to make inferences about a population based on the data collected.
Quantitative research uses numerical data to answer “where,” “when,” and “what” questions. It is the opposite of qualitative research, which uses nonnumerical data (e.g., text, audio and video recordings, and photographs). Quantitative methods are objective. Although no research is free from bias, the aim of quantitative research is ...
Quantitative research stands as a powerful research methodology dedicated to the systematic collection and analysis of measurable data. Through rigorous statistical and mathematical techniques, this method extracts insights from structured surveys, controlled experiments, or other defined data-gathering methods.
Quantitative research is the process of collecting and analysing numerical data. It can be used to find patterns and averages, make predictions, test causal relationships, and generalise results to wider populations.
Quantitative research is a systematic empirical inquiry of observable phenomena through numerical data collection, statistical analysis and mathematical models.
Quantitative research is a systematic and structured approach to gathering, analyzing, and interpreting numerical data in order to understand and explain phenomena. It involves the collection of objective, measurable data that can be quantified and analyzed using statistical methods.
Quantitative research. Quantitative methods allow us to learn about the world by quantifying some variation(s) in it. Example: how do suicide rates vary across demographic categories (Durkheim)? In order to learn about the world, we use. inference: General definition: “Using facts you know to learn about facts you don't know” (Gary King)
Abstract. Quantitative research methods are concerned with the planning, design, and implementation of strategies to collect and analyze data.