Work through the list without notes. If you cannot do a statement, follow its link, then come back. Guide = study guide; Practice = practice questions.
Understanding
- I can explain why a statistic varies from sample to sample and what a sampling distribution shows. (Guide: “Statistics vary from sample to sample”; Practice Q1)
- I can tell apart the population distribution, the distribution of one sample and a sampling distribution by saying what one value represents. (Guide: “Three different distributions”; Practice Q1, Q7(a))
- I can state the central limit theorem and explain that it is about sample means, not the data in a sample. (Guide: “The central limit theorem”; Practice Q2, Q7(a))
- I can explain the difference between the sample size n and the number of simulated samples. (Guide: “Common misconceptions”; Practice Q7(b))
Skills
- I can list every possible sample from a small population and build the exact sampling distribution of a statistic. (Guide: Worked example 1; Practice Q4)
- I can describe how to carry out one trial of a simulation from an assumed parameter value. (Guide: Worked example 2; Practice Q5(a))
- I can describe how one random reallocation is done for a randomization distribution. (Guide: Worked example 3; Practice Q6(a))
- I can describe a simulated sampling or randomization distribution by shape, centre and variability, in context. (Guide: Worked examples 2–4; Practice Q5(b), Q6(b))
Reasoning
- I can use a simulated distribution to judge whether an observed statistic is unusual, counting results as extreme or more extreme. (Guide: Worked examples 2 and 3; Practice Q5(c), Q6(c))
- I can describe how the centre, variability and shape of the sampling distribution of x̄ change as n increases. (Guide: Worked example 4; Practice Q3, Q5(d), Q7(c))
- I can explain why a randomization distribution is centred near 0. (Guide: Worked example 3; Practice Q6(b))
All ticked? Move on to Topic 3.1, Estimators, or return to the course roadmap.