Exam Preparation » Paper 3/4 investigation techniques

What you'll learn this session

Study time: 30 minutes

Key investigation techniques required for Paper 3/4
How to collect primary and secondary data effectively
Different sampling methods and when to use them
Data presentation techniques and their advantages
How to analyse geographical data
Common pitfalls to avoid in your investigation

Investigation Techniques for Paper 3/4

Paper 3/4 of your iGCSE Geography exam tests your ability to conduct geographical investigations. You'll need to show that you can collect, present and analyse data, then draw valid conclusions. This guide will help you master the key techniques needed to excel in this paper.

Key Definitions:

Primary data: Information you collect yourself through fieldwork.
Secondary data: Information collected by someone else that you use in your investigation.
Sampling: Methods used to select a manageable portion of data from a larger population.
Qualitative data: Descriptive information that can't be measured with numbers.
Quantitative data: Numerical information that can be measured and analysed statistically.

🔬 Primary Data Collection

Primary data is collected by you during fieldwork. It's fresh, relevant to your specific investigation and gives you control over how it's collected. Here are some common methods:

Questionnaires: Ask people specific questions about their experiences or opinions
Field sketches: Draw what you see to record landscape features
Environmental quality surveys: Rate areas based on specific criteria
Land use mapping: Record how land is being used in an area
Pedestrian/traffic counts: Count people or vehicles at specific locations
Measurements: River width/depth, beach profiles, soil samples, etc.

📊 Secondary Data Collection

Secondary data comes from existing sources. It saves time and can provide historical context or cover larger areas than you could study yourself:

Census data: Population statistics from government surveys
Maps: OS maps, GIS data, historical maps for comparison
Weather records: Temperature, rainfall and other climate data
Newspaper articles: For information about events or local issues
Websites: Government, academic, or organisational resources
Photographs: Historical images for comparison studies

Sampling Methods

When collecting data, you often can't measure everything, so you need to take samples. The method you choose depends on what you're investigating and the time/resources available.

🔳 Random Sampling

Every location has an equal chance of being selected.

Good for: Unbiased overview of an area

How to do it: Use random number generators or grid references

Example: Randomly selecting 20 points in a field to measure soil pH

🔳 Systematic Sampling

Taking samples at regular intervals.

Good for: Covering an area evenly

How to do it: Measure at set distances (e.g., every 10m)

Example: Taking measurements every 5m along a river

🔳 Stratified Sampling

Dividing the population into groups and sampling from each.

Good for: Areas with distinct zones

How to do it: Identify zones, then sample from each

Example: Sampling from different socioeconomic areas in a city

Data Presentation Techniques

How you present your data is crucial for clear communication. Different types of data require different presentation methods.

📈 Quantitative Data Presentation

For numerical data, consider these methods:

Bar charts: Good for comparing discrete data across categories
Line graphs: Ideal for showing changes over time or distance
Scatter graphs: Perfect for showing correlation between two variables
Pie charts: Useful for showing proportions of a whole
Choropleth maps: Maps shaded to show statistical variables
Proportional symbols: Symbols sized according to data values

📝 Qualitative Data Presentation

For descriptive information, try these approaches:

Word clouds: Visual representations of text data
Annotated photographs: Images with explanatory notes
Field sketches: Drawings that highlight key features
Flow charts: Show processes or connections
Mind maps: Organise related concepts visually
Quotes: Direct statements from interviews or surveys

Data Analysis Techniques

Collecting and presenting data is only part of the process. You need to analyse it to draw meaningful conclusions.

Statistical Analysis

Simple statistical techniques can help you identify patterns and relationships in your data:

🔢 Mean, Median, Mode

Different ways to find the average value in your data.

Mean: Add all values and divide by number of values

Median: Middle value when data is arranged in order

Mode: Most frequently occurring value

🔢 Range and Interquartile Range

Measures of spread in your data.

Range: Difference between highest and lowest values

Interquartile range: Range of the middle 50% of data

🔢 Spearman's Rank

Tests the strength of correlation between two sets of data.

Values range from -1 (perfect negative correlation) to +1 (perfect positive correlation)

0 indicates no correlation

Case Study Focus: River Investigation

A typical river investigation might involve measuring changes in channel characteristics from source to mouth:

Data collection: Measure width, depth, velocity and bedload size at regular intervals (systematic sampling)
Data presentation: Line graphs showing how each variable changes with distance downstream
Analysis: Calculate means for each site, look for patterns and use Spearman's Rank to test the correlation between distance downstream and channel characteristics
Conclusion: Relate findings to geographical theory (e.g., Bradshaw Model) and explain any anomalies

Common Pitfalls and How to Avoid Them

Many students make similar mistakes in their investigations. Here's how to avoid them:

⚠ Data Collection Issues

Insufficient data: Collect enough samples to make your findings reliable
Bias in sampling: Use appropriate sampling techniques to avoid bias
Inconsistent methods: Use the same techniques throughout your investigation
Poor record-keeping: Note down all your methods and findings clearly
Weather conditions: Consider how weather might affect your results

⚠ Analysis and Conclusion Issues

Confusing correlation with causation: Just because two things correlate doesn't mean one causes the other
Ignoring anomalies: Discuss unexpected results and possible explanations
Not linking to theory: Connect your findings to geographical concepts and models
Overgeneralising: Be cautious about making broad claims from limited data
Not evaluating methods: Discuss limitations and suggest improvements

Exam Success Tips

To excel in Paper 3/4, remember these key points:

Justify your choice of methods - explain why they were appropriate
Always include titles, labels and keys on graphs and maps
Discuss the reliability and limitations of your data
Use geographical terminology correctly
Support conclusions with evidence from your data
Suggest improvements or extensions to your investigation

Summary

Paper 3/4 tests your ability to think like a geographer by designing and carrying out investigations. By mastering the techniques covered in this guide, you'll be well-prepared to collect, present and analyse geographical data effectively. Remember that a good investigation follows a logical sequence: ask a question, collect appropriate data, present it clearly, analyse it thoughtfully and draw evidence-based conclusions.