Statistical sampling

Section S1

1 spec leaf

Notes and three levels of exam-style practice for each registered specification leaf in this section.

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S1.1

Understand and use the terms 'population' and 'sample'; use samples to make informal inferences about the population; use sampling techniques including simple random and opportunity sampling; select or critique techniques in context.

The population is the complete set about which an inference is required; a sample is the subset from which data are actually collected.
A simple random sample gives every member an equal selection chance; systematic sampling uses a fixed interval after a random start, while stratified sampling preserves chosen population proportions.
Quota sampling fills category targets without random selection, whereas opportunity sampling uses whoever is available; both are quick but vulnerable to selection bias.
When drawing an informal inference, discuss representativeness, sampling frame, non-response and sample size; a large biased sample is not automatically reliable.

Tier 1 · Easy

2 marks

ORIGINAL

A college wants to estimate the weekly study time of all $1840$ students. It records the study time of $75$ students. State the population and the sample.

Tier 2 · Standard

3 marks

ORIGINAL

A theatre has a numbered list of its $1260$ members. Describe how to select a simple random sample of $60$ members.

Tier 3 · Hard

5 marks

ORIGINAL

To estimate support for extending library opening hours, a researcher asks the first $120$ people entering the library after $8$ pm. Of these, $96$ support the proposal. Critique the sampling method and the inference that about $80\%$ of all town residents support the proposal.