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 what a hypothesis test is for, and how it differs from estimating with a confidence interval. (Guide: “What a hypothesis test does”)
- I can explain that H₀ is the status quo, assumed true unless the data give convincing evidence against it, and that Hₐ is the researcher’s suspicion. (Guide: “Writing the hypotheses”; Practice Q1)
- I can explain why the normality check for a test uses p₀ and not p̂. (Guide: “The three conditions”; Practice Q2)
Skills
- I can recognise when a one-sample z-test for a population proportion is the right procedure, and name it in full. (Guide: “Choosing the procedure”; Practice Q5)
- I can define the parameter p in context, naming the population and the response variable. (Guide: “Defining the parameter”; Practice Q3)
- I can write H₀: p = p₀ and the correct alternative, and say whether the test is one-sided or two-sided. (Guide: Worked examples 1 and 2; Practice Q4)
- I can write hypotheses for an “at least” or “at most” claim by testing at the boundary value. (Guide: “Writing the hypotheses”, rule 4; Practice Q4(a))
- I can check the random, 10% and normality conditions in context, with numbers. (Guide: Worked example 1; Practice Q5)
- I can find the smallest sample size that meets the normality condition. (Guide: Worked example 2; Practice Q6)
Reasoning
- I can decide whether a z-test is appropriate when a condition fails, and suggest a fix. (Guide: Worked example 2; Practice Q6)
- I can choose the direction of Hₐ from the question’s wording, never from the sample result. (Guide: “Writing the hypotheses”, rule 3; Practice Q7)
- I can find and correct errors in someone else’s test set-up. (Practice Q7)
All ticked? Move on to Topic 3.6, p-Values, or return to the course roadmap.