A Level Maths: Statistical Sampling Topic Summary and Resources
Video Lessons
Watch alongside the worksheet for the full lesson experience, then test your understanding with the lesson questions.
Revision Notes
Handwritten notes summarising the key ideas for each lesson. Ideal for quick review before a test.
Exam Questions
Past-paper-style questions organised by topic, with full mark schemes.
Drawn from OCR and Edexcel past papers but designed to be useful for students of all UK exam boards — including AQA and OCR MEI — unless a sheet is explicitly board-specific.
Before You Start This Topic
It will help if you are confident with the following:
- GCSE Maths Statistics — basic understanding of averages and data is assumed
- GCSE Maths Probability — useful for thinking about randomness in sampling
A Level Maths statistical sampling is the introduction to inferential statistics in the Statistics strand. You learn the different ways of choosing a sample from a population, the advantages and disadvantages of each, and how the sampling method affects the conclusions you can draw. This is the foundation for everything you do in Binomial Hypothesis Testing, hypothesis tests on the mean, and the large data set work.
You meet five sampling techniques: simple random sampling (everyone has equal chance of selection), systematic sampling (every $k$th member), stratified sampling (divide into groups, then sample proportionally from each), quota sampling (sample until specific quotas are met), and opportunity (convenience) sampling (pick whoever is available). You learn the strengths and weaknesses of each — for example, simple random is unbiased but impractical for large populations, while opportunity sampling is quick but introduces bias. You also distinguish between a population (everyone of interest) and a sample (the subset you actually study), and learn to comment critically on which sampling method is appropriate for a given investigation.
Statistical sampling is part of the Statistics strand of A Level Maths for AQA, Edexcel, OCR, and OCR MEI students.
Watch out for…
A few things to be careful with: questions often ask for advantages AND disadvantages — make sure you give both; do not confuse 'population' (everyone of interest, often impractical to access) with 'sampling frame' (the list from which you actually sample); opportunity and quota sampling can produce very biased samples and are usually criticised in exam answers; and for stratified sampling, the sample sizes from each stratum must be in the SAME proportion as the strata in the population.