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Scatter graphs show the relationship between two variables and are used to identify correlation. Students plot data, draw lines of best fit, and use them to make predictions, while understanding the limitations of extrapolation.
Students make these errors again and again. Knowing them in advance gives you a head start.
Confusing correlation with causation
Drawing a line of best fit that does not pass through the mean point
Extrapolating too far beyond the data range and assuming the trend continues
Insights pulled from Cambridge IGCSE (0580) examiner reports — the exact mistakes candidates make every year.
In probability without replacement, the denominator DECREASES by 1 for each subsequent pick (13 → 12 → 11...). Getting 104/169 instead of the correct answer usually means you forgot this.
Source: CIE 0580 · Feb/March 2024 · Paper 2 · Q25
For 'exactly one green button' out of two picks, there are TWO orderings: green-then-not OR not-then-green. Calculate one product and DOUBLE it (or add both products).
Source: CIE 0580 · May/June 2023 · Paper 4 · Q15
In a histogram, bar HEIGHT = frequency density (frequency ÷ class width). Find the scale using a bar whose frequency AND width you know, then apply it to the others.
Source: CIE 0580 · Feb/March 2022 · Paper 4 · Q5b
Based on 3of 500+ insights extracted from CIE 0580 examiner reports (2018–2024).
This topic appears in the Cambridge IGCSE past papers. Our AI tutor can help with it on any question.
Useful for this topic:
Averages are fundamental to data analysis. Students must calculate mean, median, mode and range from raw data, frequency tables and grouped data, and understand which average is most appropriate in different contexts.
Box plots (box-and-whisker diagrams) display the five-number summary of a dataset and are ideal for comparing distributions. Students draw, interpret and compare box plots, calculating the interquartile range and identifying skewness.
Sampling methods determine how data is collected for a statistical investigation. Students must understand random, systematic and stratified sampling, and evaluate the strengths and limitations of each method.
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Worked examples and data interpretation guides