The statistics paper opens with sampling and data presentation, and its questions reward precise definitions applied to concrete scenarios — exactly the format this quiz uses throughout.
The sampling questions cover the specification's method list through realistic setups: stratified sampling computed properly (50 students from a school of 1000 split 400/600, giving 20 from Year 12 by proportion), the advantages of systematic sampling (efficiency and even coverage), and the limitations of quota sampling — non-randomness and researcher judgement — tested against plausible-sounding non-issues.
The data-presentation questions anchor the two representations examiners test most: frequency density as frequency over class width, the definition that makes histograms with unequal intervals readable, and the box in a box plot as the interquartile range from Q1 to Q3.
The measures questions carry the analytical weight: the properties of standard deviation (outlier sensitivity, spread about the mean) tested against false claims — a question tightened during verification because "unaffected by adding a constant" is genuinely true of standard deviation and had to be replaced with an unambiguous falsehood — and the linear-transformation result that multiplying every value by 2 doubles both mean and standard deviation. Data cleaning appears through which corrections are statistically justifiable: removing recording errors and fixing values against source documents, never trimming inconvenient genuine observations.
Correlation and regression close the set with the two interpretive skills the specification names: reading r = 0.95 as strong positive linear association (not causation, not slope), and the primary risk of extrapolation — assuming the fitted trend continues beyond the data.
Every explanation states the definition being applied, which is exactly what the short-answer statistics questions require.
Topic scope follows sections K–L (Statistical sampling; Data presentation and interpretation) of the DfE's prescribed AS and A level mathematics subject content — 100% common across all exam boards: sampling methods, histograms, box plots, measures of location and spread, cleaning data, correlation and regression.
A researcher wants to survey 50 students from a school of 1000, divided into Year 12 (400 students) and Year 13 (600 students). If they use stratified sampling, how many students should be selected from Year 12?
20
Stratified sampling requires the sample to be proportional to the population size. The proportion of Year 12 students is 400/1000 = 0.4. Thus, 0.4 * 50 = 20 students.