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Quiz yourself on Fieldwork Process and EnquiryGet your flashcardsBuild my revision planTrack my progress๐ Statistical Analysis
Statistical tools allow you to move beyond description ("the data shows a general increase") to rigorous analysis ("the data shows a strong positive correlation, confirmed by a Spearman's rank coefficient of +0.85, which is statistically significant at the 95% confidence level"). These tools are part of the OCR B, AQA, and Edexcel specifications and are directly examinable.
Measures of Central Tendency
These summarise the typical value in a dataset:
- Mean: Add all values and divide by the number of values. Best used when data is normally distributed with no extreme outliers. A single very large or very small value will skew the mean significantly.
- Median: The middle value when data is arranged in order. More robust than the mean when outliers are present โ a single extreme reading cannot shift it significantly.
- Mode: The most frequently occurring value. Most useful for categorical data (e.g., the most common land use type on a transect).
Measures of Spread
These describe how variable the data is:
- Range: Maximum value minus minimum value. Simple but sensitive to outliers โ one extreme value inflates the range.
- Interquartile range (IQR): The range of the middle 50% of values (Q3 minus Q1). Far more meaningful than the range when outliers are present, because it focuses on the bulk of the data.
Spearman's Rank Correlation Coefficient (rs)
Spearman's rank tests whether there is a statistically significant relationship between two sets of ranked data. It is the statistical technique most commonly tested in GCSE geography fieldwork questions.
How it works:
Interpreting rs
| rs value | Interpretation |
|---|---|
| +0.81 to +1.0 | Strong positive correlation โ as Variable A increases, Variable B consistently increases |
| +0.41 to +0.80 | Moderate positive correlation |
| +0.01 to +0.40 | Weak positive correlation |
| 0 | No correlation |
| โ0.01 to โ0.40 | Weak negative correlation |
| โ0.41 to โ0.80 | Moderate negative correlation โ as Variable A increases, Variable B decreases |
| โ0.81 to โ1.0 | Strong negative correlation |
Percentage Change
To compare change over time or between sites: Percentage change = ((New value โ Old value) / Old value) ร 100
A positive result means an increase; a negative result means a decrease. This allows fair comparison between sites with different starting values.
Identifying and Explaining Anomalies
An anomaly is a data value that does not fit the overall trend โ either higher or lower than expected. Anomalies are not mistakes to be hidden; they are evidence to be explained. In the exam, identifying an anomaly and offering a geographical explanation for it often earns two or three additional marks. Common explanations include local site conditions, measurement errors on the day, or genuine exceptions to the geographical model being tested.
Quick Check: A student calculates a Spearman's rank value of +0.76 for their river velocity investigation. What does this tell them?
A Spearman's rank value of +0.76 indicates a moderate to strong positive correlation between the two variables being compared โ meaning that as one variable increases, the other tends to increase as well. In a river velocity investigation, this would support the hypothesis that velocity increases with distance downstream. However, the student should check this against the critical value table for their sample size to determine whether the correlation is statistically significant at the 95% confidence level. It is not a perfect correlation (+1.0), so some variation exists that the investigation should acknowledge in its evaluation.
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