Analysing Results (OCR GCSE Geography B (Geography for Enquiring Minds)): Revision Notes
Analysing Results
After collecting and presenting your fieldwork data, the next crucial step is analysis. This stage involves carefully examining your data to spot patterns, connections, and trends that help answer your enquiry question. Analysis transforms raw data into meaningful geographical understanding.
What is data analysis?
Data analysis is the process of making sense of the information you've gathered during fieldwork. Rather than just describing numbers or observations, analysis helps you explain what the data reveals about geographical processes and patterns.
Analysis involves four key activities:
- Spotting patterns or trends – looking for things that happen repeatedly or follow a consistent direction
- Finding relationships between variables – examining how one factor might change alongside another
- Comparing different locations or groups – identifying spatial variations across your study area
- Connecting findings to geographical theory – linking your results to processes and concepts you've learned about
The key difference is that analysis moves beyond simply describing what you found to explaining what it means geographically.
Analysis is not just about presenting numbers or observations – it's about interpretation. Your role is to explain the geographical significance of your findings and connect them to broader concepts and theories.
Identifying patterns and trends
One of your first tasks when analysing results is searching for patterns in your data. A pattern is something that occurs repeatedly or shows consistency across your measurements.
River Study Example: Identifying Downstream Patterns
In a study investigating river characteristics, you might identify these patterns:
- River width gets progressively larger as you move downstream
- River velocity increases at sites further downstream
Geographical Significance: These patterns are significant because they support established geographical theory about how river characteristics change along their course. Rivers typically become wider and faster downstream due to increased discharge from tributary inputs.
Exam Tip: When describing patterns, use precise geographical vocabulary. Say "increases downstream" rather than "gets bigger as you go along the river."
Identifying relationships
Analysis frequently involves examining how two variables relate to each other. A relationship exists when changes in one variable correspond with changes in another variable.
Urban Geography Example: Distance-Pedestrian Relationship
In an investigation of urban land use patterns, you might discover:
- As distance from the city centre increases, pedestrian counts decrease
Analysis: This shows a negative relationship – as one variable goes up, the other goes down.
Scatter graphs are particularly useful for identifying and displaying relationships between variables. They can reveal whether relationships are:
- Positive (both variables increase together)
- Negative (one increases as the other decreases)
- Non-existent (no clear pattern)
Exam Tip: Always describe the type of relationship (positive, negative, or none) and use data evidence to support your statement.
Comparing results
Spatial comparison is a fundamental geographical skill. By comparing data from different sites or locations, you can identify geographical variations and differences.
Common comparisons in fieldwork include:
- Upstream vs downstream river sites – comparing physical characteristics at different points along a river
- Two different beaches – contrasting coastal features, processes, or sediment characteristics
- City centre vs rural areas – examining differences in land use, environmental quality, or human activity
These comparisons help you understand spatial differences – how geographical features or human activities vary from place to place. For example, comparing sediment size at two beach locations might reveal the impact of longshore drift or wave energy differences.
Exam Tip: When making comparisons, structure your answer clearly by discussing each location separately, then explicitly stating the difference or similarity between them.
Using geographical knowledge
Strong analysis always links fieldwork findings back to geographical processes and theory. This connection makes your analysis more meaningful and demonstrates geographical understanding.
Coastal Processes Example: Explaining Sediment Size Variation
Observation: Your beach study shows that sediment becomes progressively smaller along the coast from west to east.
Explanation Using Geographical Knowledge: You would explain this using your knowledge of longshore drift. This coastal process gradually transports and breaks down sediment through repeated wave action, causing particle size reduction over distance.
Significance: By connecting your fieldwork observations to established geographical concepts, you show that your results make sense within the broader context of physical geography.
Exam Tip: Use technical geographical terminology when explaining processes. This shows sophisticated understanding and earns higher marks.
Using statistical techniques
Simple statistical methods can strengthen your analysis by providing numerical evidence for patterns. At GCSE level, you should be familiar with three basic techniques:
Mean (average)
The mean summarises a set of values by calculating the typical or central value. It's calculated by adding all values together and dividing by the number of values.
Use: Comparing average conditions between sites (e.g., average pebble size at Beach A vs Beach B)
Range
The range shows the spread of your data by calculating the difference between the highest and lowest values.
Use: Demonstrating variability or consistency in measurements (e.g., a large range suggests inconsistent data)
Correlation
Correlation indicates whether a relationship exists between two variables and how strong that relationship is.
Use: Testing whether variables are linked (e.g., does distance from source correlate with river width?)
These techniques provide evidence for patterns in your data, making your analysis more objective and reliable. However, numbers alone are not enough – you must always interpret what they mean in a geographical context.
Exam Tip: When using statistics, always interpret what they mean – don't just calculate and quote numbers without explanation.
Referring back to the enquiry question
Throughout your analysis, constantly link your findings back to your original enquiry question. This ensures your analysis stays focused and relevant.
Example Structure: Focused Analysis
Enquiry question: How does river velocity change downstream?
Analysis approach:
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Present evidence: "Velocity measurements increased at each downstream site, from 0.3 m/s at Site 1 to 0.8 m/s at Site 4"
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Explain the pattern: "This supports geographical theory that rivers become more efficient downstream as discharge increases from tributary inputs and channel size grows"
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Answer the question: "Therefore, velocity does increase downstream, supporting the predicted pattern"
Why this works: This focused approach ensures your analysis directly addresses what you set out to investigate, making your fieldwork more coherent and purposeful.
Exam Tip: In exam questions asking about analysis, examiners want to see clear links between your data, geographical theory, and your enquiry question.
Remember!
Key Points to Remember:
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Analysis interprets data – it explains what your results show and what they mean geographically, not just what numbers you collected
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Look for patterns, relationships, and spatial differences – these are the building blocks of geographical analysis
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Link findings to geographical processes – connect your results to theory you've learned (e.g., river processes, coastal processes, urban land use models)
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Use statistical techniques appropriately – mean, range, and correlation provide numerical evidence to support your observations
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Always refer back to your enquiry question – keep your analysis focused on what you originally set out to investigate