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Section 3 - Data Presentation

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Edexcel geography a-level, fieldwork section 3 - data presentation, essential notes, introduction.

This is a comprehensive guide to the many ways of presenting data. It is necessary to take your raw data and produce tables, graphs and use statistical analysis techniques (discussed in a separate document) to discuss relevant data. Very little marks are awarded for your choice of presentation technique; however, your mark will be limited if there is not a range of presentation methods used. The techniques we’ll discuss are below:

Graphs and Charts

● Bar charts ● Pie charts ● Radar Graphs ● Line Graphs ● Histograms ● Box Plots ● Kite Diagrams ● Pictograms ● Triangular Graphs ● Scatter Graphs ● Logarithmic Scales ● Lorenz Curve

Cartography

● Map and Image Overlays ● Isoline Maps ● Dot Maps ● Choropleth Maps ● Flow Lines

Qualitative Presentation

● Photographs ● Quotes/Mindmaps

Numerical Analysis

● Central Tendency ● Dispersion

It should be noted that some data within this guide has been created and manipulated to show the data presentation methods, and is not entirely accurate. Unless the graph has been taken from an external source (as referenced) it should be assumed that the data within the figure is false. This data has been manipulated to show clear data presentation methods that will serve as an educational resource for data presentation, rather than resources you can use as valid sources

within your investigation.

● The colours are clear and the different segments could be identified if the document was printed in greyscale (patterns are useful) ● The key is explicit and easy to understand ● There are not too many segments

Radar Graphs

Radar graphs are most effective at displaying data from environmental quality surveys, or data about different locations. Data from various locations can be overlaid or compared on different charts. It is important that all of the scales are in the same direction. All of the positive, highest scores should be in the same area of the graph (either all in the middle or all surrounding the outside). For example, rather than having quiet, welcoming, and unsafe all on the outside, it should be quiet, welcoming, and safe as shown in the radar graph. There is no limit to the amount of data sets that you can use, but using too many sets may make the graph confusing.

Similar to a radar graphs, rose graphs use multi-directional axes to represent data, but with bars instead of lines. Rose graphs use compass directions for the axes directions, and you should define how far from a central point you are measuring when collecting the data. They could be useful for assessing forest cover (light levels), noise levels or wind speed, though there are many other possibilities. If you were investigating noise in a city centre area, you could use a rose graph over a wider area (10 metres in each direction).

Line Graphs

Line graphs are useful for tracking a change, usually over time. In line graphs, the change that is being tracked will usually be a gradual change so that every point can be joined up in one line. A key could be used to track how several factors change over the same period.

Source: pubs.usgs/fs/2009/3046/

Line graphs may be simplistic as stand alone graphs, but can also be used in combination graphs. For example, Flood Hydrographs use bar charts (precipitation) and line graphs (river discharge). You can create combination graphs by selecting ‘Combo Chart’ in data formatting programmes.

Histograms are simply bar charts of varying thicknesses; for data with different class widths, a histogram is most appropriate. The area of a histogram’s bar (the frequency density multiplied by the class width) is the frequency of your reading. For example, in the figure, the red box represents a frequency of 15 people between the height of 90cm and 105cm. There are histogram generators online, or use Excel - type all your data into a table, then highlight the table and click insert statistical chart. Source: pythagorasandthat.co

Box plots (sometimes called a Box and Whisker graph) are a pictographic way to represent the median, range and interquartile range. They are used to compare the spread of results and can be used to compare multiple sets of continuous data. A box plot is easy to draw: 1. Draw an appropriate scale horizontally - Make sure your scale includes your maximum and minimum results, and should be for the variable you measured (e. the height of waves, time taken to erode, etc)

Plotting points - to plot points, your value should be halved and each half should be plotted on either side of the mirror line. This will create a symmetrical shape when all the points are plotted and joined up.

Labelling - all of your sections should be labelled with the factor you are measuring and the distance of the transect. On your y axis, you should also label numbers. Make sure to label the zero line (mirror line) and the maximum value (half the highest value). All of the sections (daisy, dandelion etc.) should be the same size so that you can compare. Do not change the size of the sections on the same graph. Always use the biggest number in the entire set of data to work out how wide your section should be.

Pictograms use icons or pictures to display sets of discrete data (data that has a finite count, i. cannot have a decimal point). Each icon represents a number, so that a completed pictogram will show the frequency of a factor in different sets of data. The icon usually resembles what is being counted. Here is an example of a completed pictogram that has been created from a building use survey.

A pictogram showing the different types of buildings on Main Street:

Residential 18 Key:

Overall - 41, buildings on, main street.

Commercial 8

Entertainment 5

Public Building

Transport 2

Pictograms are useful for presenting simple counts in interesting and understandable ways. However, pictograms can become confusing when there are many numbers involved because it would require counting many icons, which is unclear. To present larger counts, a key could be used which condenses down the counts into ratios (e. 1 icon = 10 buildings) but in doing this, you must ensure your counts all have the same highest common factor. For example, if you want to use a key of 1 icon = 10 buildings, your different building counts should all divide by 10. Using half icons or quarter icons to represent a smaller number becomes messy and confusing, so generally it is best to stay away from pictograms when many numbers are involved.

Triangular Graphs

Triangular graphs compare the composition of different data sets by using 3 variables that add to 100%. Each data set is plotted as a point on the triangular axis shown.

Each axis (side of the triangle) goes up to 100%. The data you plot must be composed of 3 variables that collectively and exclusively add to make 100%.

For example, a triangular graph could be used to show soil content in 10 different locations (the data sets). In these 10 different areas, the soil content is mainly a mixture of clay, silt and sand. Here is how some areas would be plotted on a triangular graph.

Area 1: Clay - 70%, Silt - 20%, Sand - 10%.

Area 2: Clay - 50%, Silt - 10%, Sand - 40%.

The easiest way to plot points is to read horizontally from the left axis, then diagonally downwards from the right axis, then diagonally upwards from the bottom axis. Ensure you label each point plotted as well as each axis.

Furthermore, you could split your graph up into predetermined definable areas, so that wherever your points lie indicates what your point could be defined as. Here is an example:

Source: oneplan/Water/soil-triangle.asp

When your points are plotted, the graph easily show what the composition of your data set means in a geographical context.

Scatter Graphs

Scatter graphs are used to show the relationship or correlation between an independent variable and a dependent variable. Every piece of data is plotted like a coordinate on an axis: the x axis is the independent variable, i. the cause. The y axis is

logarithmic scale goes up by 1. This table shows the logarithmic scale that would be created when inputting certain numbers, and it also shows what would appear on your calculator when typing your raw data in.

Raw number log 10 (x) format Number that is used in your scale

10 log 10 (10) 1

100 log 10 (100) 2

1000 log 10 (1000) 3

10000 log 10 (10000) 4

The Richter scale is an example of a logarithmic scale , where a 4 magnitude earthquake is 10 times stronger than a 3, 100 times stronger than a 2, and 1000 times stronger than a 1.

This scale is very useful when your raw data has a very large range, because it ensures smaller numbers are still clear. For example, this scale would be useful if some of your figures were in triple digits, and other figures were in six digits. In these two graphs, house price data in 5 towns is being compared. Note how the comparison is much clearer to see on the logarithmic scaled graph.

Without logarithmic scale. With logarithmic scale.

If logarithmic scales are used, make sure that you indicate this to avoid confusion.

Lorenz Curves

A lorenz curve is a graphical representation of the distribution or equality of something. A straight, diagonal line from the origin represents perfect equality. The further away the lorenz curve is from this, the more diverse the sample is and the more unevenly the values are spread out. From a Lorenz curve, the Gini Coefficient can be calculated.

Rank the data

Order the data by Rank

Calculate the proportion (percentage) of each data from the total data

Calculate the cumulative proportion by increasing rank (calculate the running total from adding the percentage of each line in turn to the line before it)

Graph the ranks on the x axis against the cumulative proportion on the y axis.

Draw the perfect equality diagonal line.

Cartographical Data Presentation Methods

A GIS (geographic information system) is a form of data analysis and presentation. Any digital presentation of data in comparison to its location or spatial distribution can be classed as GIS. For colleges with GIS software, this is often simple to create (so see your teacher for more specific guidance). For those without specific GIS software, any of the cartographic data presentation methods may be considered GIS, if you create them digitally rather than drawn by hand.

GIS is more accurate than hand drawing, as it minimises the risk of human error in drawing graphs or pinpointing locations. It can enable you to display a large data set, or multiple variables/ information. For example, for each location sampled, a bar chart could display the average scores of several questions on an environmental survey or differing demographic characteristics along the rural-urban continuum. GIS is a key addition to create a high-level fieldwork report that looks scientific and reliable.

Map Overlays

Overlaying graphs or other data such as pie charts on to maps can be a powerful tool to easily display data. This map uses proportional pie charts and Google Maps, to display footcount survey data. The larger the pie chart, the greater the number of people that were surveyed in the 10 minute data collection period at the: Stockholm Town Hall, Riddarholmen Church and Stockholm Middle-Ages Museum. The various colours represent the different proportions of people by age (years) in each survey location.

Key: 0- 16- 31- 46+

Map Credit (Google, 2018)

where there is a lack of data, which makes isoline maps useful. However, it is also important to consider as estimating values can lead to inaccuracies and may disregard trends. The 10 line separates numbers 10 and below from higher numbers. The 20 line separates all values below or equal to 20 but more than 10. The 30 line separates all values below or equal to 30 but more than 20, and so on. To make the isoline map even clearer, a colour code could be added to emphasise the different sections. When using isoline maps, ensure your lines’ values increase by the same amount (e. all of the isolines increase by 10 in this example).

Isoline maps can be used for anything that shows many different geospatial values, and they are often used in weather or topography (the contour lines on maps are isolines). Take this map of the Cairngorms in Scotland for example. Each line represents elevation above sea level, and each isoline increases by 500m. The isolines get closer together when the elevation increases rapidly. Source:cairngormwanderer.wordpress/page/18/

A dot map is a cartographical data presentation technique that uses small dots on a map to show the distribution or density of an observation. Wherever you have a recorded observation, a dot is marked on that exact location on the map. If you have two observations in the same exact location, the dot can be placed slightly to the side so that it can still be seen. Eventually, the map will have enough dots that a clear pattern is shown, which indicates both spatial distribution of your observation and the density of your observation within certain areas. What to consider when using a dot map: ● Collect a large amount of data. Dot maps are only useful when you have a lot of data so that a trend in density can be spotted. If you have a small amount of dots, your trends will be unclear. Make sure to choose something you are able to make hundreds of observations in. ● Use appropriate dot sizes. If your dots are too large, they may overlap meaning observations are lost. Ideally, your dot size should be large enough to create density patterns but small enough so that (if you were to zoom in) every dot could be seen. Compare the two dot maps (Source:learngis/creating-statistical-dot-density-map-qgis/). The first dot map clearly uses dots that are too large, as all of the map is concealed and there is no density pattern. The second map uses dots that are appropriate for the dot map.

● What do your dots represent? 1 dot could represent 1 observation (1:1), or it could represent more than 1 observation (1:many). If you have a large amount of data, it may be useful to include a key where 1 dot represents more than 1 observation, e. 1: ratio, where 1 dot actually represents 10 observations. You may also wish to include a colour coordinated key, where the colours of the dots show different observations. ● Is a dot map the most appropriate method for your data? If you are recording something that has a yes/no or existent/non-existent observation, dot maps can be useful. However, if you are recording something that can be recorded on a continuum or scale, a choropleth map may be more suited.

Choropleth Map

A choropleth map uses colouring or shading in predetermined areas to show the average prevalence of a phenomenon. This factor can be recorded on a scale or continuum, and each colour indicates a different section (called data classes) of your scale.

Source:simple.wikipedia/wiki/File:Countries_by_Population_Density_in_2015 Choropleth maps are useful when analysing the intensity/prevalence/frequency of a phenomenon in different areas. Patterns can be spotted within your map, which makes choropleth maps useful for analysing factors that vary spatially.

Things to consider: ● Borders - your sectioned sub-areas should be small enough so that your average value does not ignore obvious variances within your data. Your borders should also be large enough so that you can collect a sufficient amount of data within your timeframe. If you have many small areas that show the same observation, it may be worth condensing these areas into one larger area.

Qualitative Data Presentation Methods

Photographs.

If you are using photographs as a method of data presentation then they should be clearly annotated, with information relating to your hypotheses. You may use place names, geographic theories or observations that you made when taking the photos to give them greater meaning and relate them to your investigation.

NE Ljubljana as seen from the Ljubljana Castle - It is appropriate to state which direction the photograph is taken from if known.

Map Credit: (Google, 2018)

Photographs are a great way to enrich your report and make it more stimulating to read. You may take pictures of large area, but analysing smaller areas in detail is just as important. You may want to take images of your survey sites. When taking photos consider: ● The angle which you are taking the photograph at - what does it show and what does it not show? Is it objective? ● Be careful not to photograph individual people as you do not have their permission. ● What is the area like that you are photographing? Is it safe? If not, it may be advisable to not take pictures if there is a risk, for example risk of your camera/phone being stolen.

● Can you take pictures in the same location with the same angle at different times and then compare these later? ● Could you find images online and then photograph the same place yourself? What are the differences if there are any?

You can also compare pictures that you take to maps that may be online. You can use Bing Maps to find Ordnance Survey maps, and Google maps to show terrain and different places. This creates an insightful source of data presentation.

Always annotate photographs - no marks are awarded for ‘pretty picture’!

Quotes/Mind Maps

Mind maps are another useful tool used to present a wide range of qualitative (and also quantitative) data. It may be useful when creating a mindmap to structure it around a part of the core theory - in the example above, the Hazard Management Cycle. This gives clear structure to the mind map and demonstrates your knowledge of the geographical context in your

Necessary Maths

For some of the graphs discussed previously, some simple maths values are needed for a graph to be drawn. These values are known as measures of central tendency.

The numbers below will be used as an example for each measure of central tendency.

13 25 79 82 1 45 49 45 67 45 1

Mean: The mean is calculated by adding up all the data and dividing by the number of data items. For example, using the numbers above, the sum would be 452 and there 11 numbers, so the mean would equal 41 to 3sf.

Mode: The most appearing number. In the example above, the mode is 45.

Median: The median is the midpoint value. The data needs to be ranked first from lowest to highest value.

1 1 13 25 45 45 45 49 67 79 82

● When there is an odd number of data items, the median is a whole number. As in the example above, there are 11 data items, so the median is 45. ● When there is an even number of data items, the median lies across the two items at the midpoint. The median is therefore an average (mean) of the two middle items.

Measures of Dispersion

The term ‘measures of dispersion’ refers to a group of statistical tests that describe data distribution.

Range: The range describes the spread of the data. Simply, subtract the highest number from the lowest number. In the example above, the range would be: 82-1 = 81

Interquartile range: The interquartile range shows where the middle 50% of the data lie. Anomalies should be ignored in this calculation. ● Find the median using the method above. (45) ● Find the lower quartile by calculating the median of the lower half of the data. (13) ● Find the upper quartile by calculating the median of the upper half of the data.(67) ● The difference between the lower and upper quartiles is the interquartile range.(67-13 = 54)

• Multiple Choice

Module : A Level Geography (H481)

University : exeter college, exeter.

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• A student guid...

A student guide to the A Level independent investigation (Non-examined Assessment - NEA)

The following documents are available in the Downloads section below:

Download a copy of the guide below

Lawrlwythwch gopi o'r canllaw

Before you start

i   – Independent Investigation - Student Planning Form        Independent Investigation - Student Planning Form (Word document) ii  – A Guide to Writing A Research Plan iii – A Guide to Effective Background Reading iv – A Guide to Referencing

Section 1 – Introduction

1a – A Guide to Hypotheses

Section 2 – Data collection

2a – A Guide to Different Types of Data

2b – A Guide to Data Collection Techniques – Quantitative Measuring

2c – A Guide to Data Collection Techniques – Surveys

2d – A Guide to Data Collection Techniques – Interviews

2e – A Guide to Data Collection Techniques – Questionnaires

2f – A Guide to Data Collection Techniques – Observations, Photographs and Field Sketches

2g – A Guide to Sampling Techniques

2h – A Guide to Recording Data in the Field

2i – A Guide to Avoiding Biased Data

Section 3 – Data presentation

3a – A Guide to Column Charts and Histograms

3b – A Guide to Pictograms

3c – A Guide to Pie Charts

3d – A Guide to Scatter and Line Graphs

3e – A Guide to Box and Whisker Graphs

3f – A Guide to Kite Diagrams

3g – A Guide to Triangular graphs

3h – A Guide to Rose and Radial Graphs

3i – A Guide to Isoline Maps

3j – A Guide to Choropleth Maps

3k – A Guide to Pictorial Data Presentation

3l – A Guide to Presenting Qualitative Data

Section 4 – Data analysis

4a – A Guide to Measures of Central Tendency

4b – A Guide to Measuring Proportions

4c – A Guide to Measures of Dispersion

4d – A Guide to Cost-Benefit Analysis

4e – A Guide to Spearman’s Rank

4f – A Guide to Chi-Squared Testing

4g – A Guide to Simpson’s Diversity Index

4h – A Guide to Pearson’s Product Moment

4i – A Guide to Nearest Neighbour Analysis

4j – A Guide to Mann-Whitney U Test

4k – A Guide to Qualitative Data Analysis

Section 5 – Conclusions

Section 6 – Evaluation

Section 7 – Final checks 

Posters – A guide to reading your research landscape

A copy of FAQs from the awarding bodies

View a video from the Royal Met Soc - MetLink - Weather Fieldwork for your A Level Geography Independent Investigation

File name Files

Full Guide: Guide to the NEA

Student Planning Form - Word

Student Planning Form - PDF

A Guide to Writing A Research Plan

A Guide to Effective Background Reading

A Guide to Referencing

1a – A Guide to Hypotheses

2a – A Guide to Different Types of Data

2b – A Guide to Data Collection Techniques – Quantitative Measuring

2c – A Guide to Data Collection Techniques – Surveys

2d – A Guide to Data Collection Techniques – Interviews

2e – A Guide to Data Collection Techniques – Questionnaires

2f – A Guide to Data Collection Techniques – Observations, Photographs and Field Sketches

2g – A Guide to Sampling Techniques

2h – A Guide to Recording Data in the Field

2i – A Guide to Avoiding Biased Data

3a – A Guide to Column Charts and Histograms

3b – A Guide to Pictograms

3c – A Guide to Pie Charts

3d – A Guide to Scatter and Line Graphs

3e – A Guide to Box and Whisker Graphs

3f – A Guide to Kite Diagrams

3g – A Guide to Triangular graphs

3h – A Guide to Rose and Radial Graphs

3i – A Guide to Isoline Maps

3j – A Guide to Choropleth Maps

3k – A Guide to Pictorial Data Presentation

3l – A Guide to Presenting Qualitative Data

4a – A Guide to Measures of Central Tendency

4b – A Guide to Measuring Proportions

4c – A Guide to Measures of Dispersion

4d – A Guide to Cost-Benefit Analysis

4e – A Guide to Spearman’s Rank

4f – A Guide to Chi-Squared Testing

4g – A Guide to Simpson’s Diversity Index

4h – A Guide to Pearson’s Product Moment

4i – A Guide to Nearest Neighbour Analysis

4j – A Guide to Mann-Whitney U Test

4k – A Guide to Qualitative Data Analysis

Section 7 – Final checks

Posters – A guide to reading your research landscape

Poster – RMetS weather and climate

FAQs from the awarding bodies

A Guide to Collecting Weather Data

BSG geomorphology projects for students

NEA word limit letter

Ethical Data resources

Doug Specht and colleagues from the University of Westminster have produced resources to provide some extra guidance and support around ethics and data use for the NEA

This project was funded by the Nuffield Foundation, but the views expressed are those of the authors and not necessarily those of the Foundation

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Notes || Videos || Sample Sections

Essential Notes

• Section 1 - Introduction and Preliminary Research
• Section 2 - Methodology
• Section 3 - Data Presentation
• Section 4 - Data Analysis & Critical Evaluation
• Section 5 - Writing Your Coursework

Extra Notes

• Choosing a Topic
• Data Collection Techniques
• Geographical Information Systems (GIS)

Maths Resources

• Maths for Geographers (suitable for Edexcel)
• Statistical Analysis Techniques

Referencing

• Harvard Referencing

Sample Sections

• Flood Risk Management Sample Answer (Methods)
• Rural Inequalities Sample Answer (Methods)
• Flood Risk Management Sample Answer (Analysis)
• Rural Inequalities Sample Answer (Analysis)
• Rural Inequalities Sample Answer (Conclusions)
• Mann-Whitney U
• Chi Squared
• Spearman’s Rank
• Standard Deviation
• Box and Whisker Plots
• How to use ArcGIS

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A Level Geography NEA: Everything you need to know

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What is the A Level Geography NEA?

How do you structure the geography nea, concluding remarks.

For Year 12 students, the last half term of the academic year is typically a time for reflection and taking stock of what they have learned so far. However, for geography students, this time is one of the busiest and most intense. The reason? The Geography NEA , which often kicks off after the external examination period in schools, demanding significant time and effort to complete.

NEA stands for non-examined assessment . It’s an important aspect of A Level Geography, allowing students to apply the theories they have learned and create a substantial enquiry project using both primary and secondary research. The Geography NEA is divided into manageable sections which will be assessed by your teachers at school or college.

The NEA provides an opportunity to do a deep dive into an aspect of geography that interests you the most. Your NEA must be linked to a taught aspect of the A Level Geography specification you are studying at your centre.

Each exam board provides a range of example titles and enquiries in their assessment specifications. Additionally, your centre will give you examples of projects completed by previous students. While these examples can serve as a guide, it’s important that you come up with your own enquiry question before starting your NEA.

Before starting your NEA enquiry, you will write a proposal that will be submitted to your supervisor (teacher). The proposal will include the following sections:

• Investigation title
• How the title links to the specification content
• Planned investigation hypothesis or question/sub-questions
• Investigation focus
• Planned methodology

Once you have completed your proposal form, your supervisor will review it. If the proposal is approved, you can begin your project. If it is not approved, your supervisor will provide feedback on what needs to be changed, and you will need to redraft the proposal form.

When it comes to the teacher assessment phase, each exam board has split the NEA into different sections. However, the general structure of the NEA written report is similar across the exam boards. Each completed Geography NEA should include:

• Introduction
• Literature review
• Methodology (including risk assessment and ethical considerations)
• Data presentation
• Data analysis

How do you write the NEA introduction?

The NEA introduction allows you to outline your enquiry to the reader and help them understand where and why you will be carrying out your investigation. This section should clearly state your hypotheses and key questions and provide a rationale for why you are asking these questions .

In your introduction, you should include the location details of your investigation. This gives you an early opportunity to use GIS (Geography Information Systems) by using a range of maps to demonstrate the study location.

What is the NEA literature review?

A literature review means reading geography books, websites, and journals for your NEA and referring to these sources in your report to demonstrate your understanding of geography concepts. Your fieldwork will help you determine if these ideas hold true in your chosen area. When conducting the literature review, you will need to use a range of materials that are academically sound and from reputable sources .

The research you conduct during the literature review should be referenced throughout your enquiry , including in your data analysis and conclusions. This will help you to either prove or disprove your hypotheses and key questions.

How do you write the NEA methodology?

The methodology is the part of the Geography NEA that outlines:

• what data you collected or are going to collect
• how you collected or are going to collect the data
• why you collected or are going to collect the data

The methodology can be written in either the past or future tense, depending on when you are writing it. If you have already completed your data collection, write it in the past tense. If you are going to complete it, write it in the future tense. I would suggest writing the methodology after completing your data collection . This approach will provide you with a greater understanding of the methods and the reasons for collecting that specific data.

The methodology should be written in a way that allows others to replicate your NEA in the future. It should include details such as:

• Name of method
• Description of method
• Type of data collected
• Sampling techniques used
• Justification of method – this is key to achieving the highest marks available
• Risk assessment

I recommend organising the methodology in a table with the above list as column titles. This will ensure that all key aspects are covered, giving you the best chance of achieving the highest marks.

How do you present and analyse data in the NEA?

Once you have collected your data, it’s time to present it. You can use a range of data presentation methods. Try to choose the most suitable ones to make your results easy to understand. To achieve the top marks in your Geography NEA, you need to use a wide variety of data presentation methods . I recommend looking at PMT’s guide to data presentation before you begin:

• AQA data presentation guide
• OCR data presentation guide
• Edexcel data presentation guide
• WJEC data presentation guide

This is another opportunity for you to utilise GIS . Using GIS allows you to incorporate a location element into your data presentation, which can help you achieve the highest marks in this section.

Once you have presented and transformed your raw data into a usable format, you can proceed with the analysis. Data analysis is a crucial part of your Geography NEA enquiry, as it will enable you to draw conclusions and ultimately answer your key questions and hypotheses .

If you have quantitative data, it’s important to carry out statistical tests to demonstrate the reliability of your data and conclusions. You can find examples and full walkthroughs in the PMT NEA guides to help you.

At this point, you should be ready to write about your results from your data presentation and critically analyse the data. When analysing your data, ensure that you connect it to your hypotheses or questions . Start by discussing what your data reveals about your subject, such as patterns or common opinions. In addition to overall trends, use specific numbers and quotes. You can also use this opportunity to manipulate some of the data. Thoroughly examine your data and don’t ignore any unusual points that might disprove your hypotheses.

During your analysis, you can comment on the accuracy of your data to strengthen your conclusions. For example, you could comment on the precision of your graphs to show that your data captures all trends. Additionally, you should discuss how well your data represents the study area , especially if multiple investigation sites were used. Explain the appearance of data patterns using geographical theories, and link this to your literature review . This will show that your understanding of geography has deepened through your investigation.

How do you write the NEA conclusion?

The conclusion of your Geography NEA is where you essentially answer your key questions using the data you have collected and the critical analysis you have conducted.

Start by answering each of your key questions individually, summarising the relevant analysis to directly match each question. Once you have answered the key questions, use these to address your overall hypotheses and ultimately summarise your entire enquiry, tying together the main findings and insights.

How do you write the NEA evaluation?

The final part of the NEA enquiry is the evaluation. This is generally poorly completed because it’s the final stage and candidates often run out of time and rush this section.

The evaluation is an opportunity for you to reflect on the process and comment on the reliability of your processes and results . You can discuss your methods and consider how you could improve them for more reliable results.

How long should the NEA be?

The guidance states that the A Level Geography NEA should be between 3000 and 4000 words . However, you will not be penalised if you go over this. I suggest that you do not go over the recommended word count significantly, as this will mean that you have not been writing concisely and may impact your ability to achieve the highest marks.

How many marks is the NEA worth?

The number of marks the NEA is worth varies depending on the specific exam board. For the precise mark allocation, check with your school or college.

Which section of the NEA is worth the most marks?

The data analysis section of the NEA is typically worth the most marks.

What are the grade boundaries for the NEA?

The NEA is worth 20% of your total grade for A Level Geography. Each year, the grade boundaries for the NEA vary because they are determined after all exam papers and NEAs have been assessed and analysed by the exam board.

When is the A Level Geography NEA deadline?

The deadline for the Geography NEA can vary depending on your school and exam board. Generally, the NEA is expected to be completed and submitted during the final term of Year 12 or early in Year 13, well before the final A Level exams in the summer. Starting early and managing your time effectively can help ensure you meet the deadline without any last-minute stress.

How do I get an A* in the A Level Geography NEA?

To succeed in your NEA, I would always recommend choosing a topic that genuinely interests you . This will help you stay engaged in the project, allowing you to write detailed and thorough responses and engage fully in the enquiry.

To achieve an A*, you need to consistently aim for the highest band in each element of the enquiry. I would suggest that all candidates familiarise themselves with the NEA mark scheme and use it as a guide for their writing. You also need to ensure you write succinctly and accurately throughout your project, as this will help you access the highest marks.

The NEA is a significant component of your overall A Level Geography grade, providing you with an opportunity to apply your theoretical knowledge in a practical context. The NEA demands careful planning, thorough research, and detailed analysis. By understanding the structure and requirements of each section, you can approach your Geography NEA methodically and confidently, and produce a thorough and insightful project. Good luck!

Looking for more help with A Level Geography? Check out our guide to mastering A Level Geography 20-mark essay questions !

Dave is a qualified teacher with 10 years of experience teaching GCSE and A Level Geography. He has worked as an assistant faculty leader for Humanities and a professional mentor for new and trainee teachers. He has also been involved with the supervision and guidance of NEAs. Dave currently works in higher education and trains geography teachers across the North West of England. He is also a tutor at PMT Education , with experience running highly successful geography courses .

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