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At GCSE you extend data representation to cumulative frequency graphs, box plots, histograms with frequency density, and more advanced comparison of distributions. You also study sampling methods and make inferences about populations.
Mean, median, mode and range from raw data and frequency tables — see KS3 lesson for details.
Mean from a grouped frequency table: Estimated mean = sum(f × midpoint) / sum(f)
Cumulative frequency is the running total of frequencies.
Plotting: plot (upper class boundary, cumulative frequency), then join with a smooth S-shaped curve.
| Height h (cm) | Frequency | Cumulative Frequency |
|---|---|---|
| 140 ≤ h < 150 | 4 | 4 |
| 150 ≤ h < 160 | 12 | 16 |
| 160 ≤ h < 170 | 20 | 36 |
| 170 ≤ h < 180 | 14 | 50 |
Reading off the graph:
A box plot displays: Minimum, Q1, Median, Q3, Maximum.
Comparing two distributions using box plots:
Example comparison: "Group A has a higher median (72 vs 65), so Group A performed better on average. Group A also has a smaller IQR (12 vs 20), suggesting Group A's results are more consistent."
Used for continuous grouped data where class widths may be unequal.
Frequency density = frequency ÷ class width
The area of each bar = frequency (not the height).
Reading a histogram: Frequency = frequency density × class width.
Example:
| Time t (mins) | Class width | Freq density | Frequency |
|---|---|---|---|
| 0 ≤ t < 10 | 10 | 3 | 30 |
| 10 ≤ t < 15 | 5 | 8 | 40 |
| 15 ≤ t < 25 | 10 | 5 | 50 |
| 25 ≤ t < 40 | 15 | 2 | 30 |
Total frequency = 150 Estimated mean = use midpoints 5, 12.5, 20, 32.5 with respective frequencies.
Plot the frequency against the midpoint of each class interval. Join the points with straight lines. Useful for comparing two distributions on the same graph.
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