Sampling & Inference

University 6 questions

What sampling & inference means

This skill helps you work with a smaller group to draw sensible conclusions about a larger population. You use it to read sample results, build confidence intervals and test ideas with clear reasoning.

What you will practise

Identify samples, populations, statistics and parameters
Interpret confidence intervals from sample data
Set up null and alternative hypotheses
Decide whether sample evidence supports a claim
Read basic inference questions with care

Before you start

You should already be comfortable with averages, percentages and simple probability. It also helps to know the difference between data from one group and a whole population.

Not confident yet? Work through Descriptive Statistics & Probability first.

Worked example

One question from this skill's own question bank, shown with its full working.

Question

A subset of a population selected for study is called a

sample
census
parameter
variable

Answer: sample

Working: A sample is the part of the population actually studied to make inferences about the whole.

Common mistakes to avoid

Mixing up a sample with the whole population. Check whether the question asks about part or whole.
Calling a population value a statistic. A statistic comes from sample data only.
Treating the alternative hypothesis as the no-effect statement. The null hypothesis is the one with no difference or no effect.
Using a confidence interval as exact certainty. It gives a likely range, not a guaranteed value.

Curriculum and exam alignment

Tertiary foundation coursework

This topic normally appears after basic descriptive statistics and probability in university and tertiary foundation study. It supports later coursework and professional entrance tests that require you to interpret data, make inferences and judge evidence from samples.

Curriculum notes are a general guide to where this work normally sits. Always check the syllabus your school or examination body is currently using.