Database results:
examBoard: Cambridge
examType: IGCSE
lessonTitle: Data Analysis and Evaluation
Paper 4 (Alternative to Coursework) requires you to demonstrate your ability to collect, analyse and evaluate geographical data. This crucial skill helps you turn raw information into meaningful insights that support geographical understanding.
Key Definitions:
Good data analysis allows you to:
In Paper 4, examiners are looking for your ability to:
Choosing the right way to present your data is crucial for effective analysis. Different types of data require different presentation methods.
Line Graphs: Best for showing changes over time or distance.
Bar Charts: Ideal for comparing discrete categories.
Scatter Graphs: Perfect for showing correlation between two variables.
Pie Charts: Good for showing proportions of a whole.
Choropleth Maps: Show variations across regions using shading.
Dot Maps: Display distribution patterns using dots.
Flow Maps: Show movement or connections between places.
Isoline Maps: Connect points of equal value (e.g., contour lines).
Simple Tables: Organise data in rows and columns.
Cross-tabulation: Compare two variables simultaneously.
Mean, Median, Mode: Measures of central tendency.
Range & Standard Deviation: Measure data spread.
Once you've presented your data, you need to analyse it effectively. This means looking for patterns, relationships and anomalies.
Look for these key elements in your data:
In a river study, you might notice these patterns:
Simple statistical methods can help you analyse your data more rigorously.
Mean: The average value (sum divided by count)
Median: The middle value when data is arranged in order
Mode: The most frequently occurring value
Range: The difference between highest and lowest values
These help summarise your data and identify central tendencies.
Spearman's Rank: Measures correlation between two ranked variables
Nearest Neighbour Analysis: Measures the distribution pattern of points
Chi-squared Test: Tests whether observed frequencies differ from expected frequencies
These help determine if relationships in your data are statistically significant.
A critical part of Paper 4 is evaluating the quality of your data and methods. This shows examiners you understand the limitations of geographical investigations.
Question: Would you get the same results if you repeated the study?
Issues: Sample size, equipment accuracy, consistency of methods
Example: "Our rainfall measurements may lack reliability as we only collected data for three days."
Question: Does your data actually measure what you intended to measure?
Issues: Appropriate methods, bias in questionnaires, representative sampling
Example: "Our pedestrian count may not validly represent typical footfall as it was conducted during a holiday period."
Question: What factors might have affected your results?
Issues: Weather conditions, time constraints, equipment limitations, human error
Example: "Heavy rainfall the day before fieldwork may have affected our soil infiltration results."
A student investigated temperature variations across an urban area:
The final step in data analysis is drawing meaningful conclusions that answer your original geographical questions.
In Paper 4, you might be asked to analyse unfamiliar data. Follow these steps:
Example answer: "The data shows that river velocity increases from 0.3 m/s at site 1 to 1.2 m/s at site 5, suggesting an overall downstream increase. However, there is a notable decrease at site 3 (0.5 m/s), which could be explained by the river widening at this point, creating a pool feature. The general increase in velocity downstream contradicts the Bradshaw Model, possibly because this river has been artificially straightened in its lower course."
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