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 the two-sample t-statistic measures, in standard errors from 0. (Guide: “The test statistic”)
- I can explain why the p-value is calculated assuming the two population means are equal. (Guide: “Interpreting the p-value”; Practice Q2)
- I can explain why failing to reject H₀ does not show the means are equal. (Guide: Worked example 2; Practice Q3, Q7)
- I can explain why conservative degrees of freedom give a slightly larger p-value. (Guide: “Degrees of freedom and the p-value”; Practice Q4)
Calculation
- I can calculate the standard error and t-statistic from summary statistics or raw data. (Guide: Worked examples 1 and 2; Practice Q1, Q5, Q6)
- I can find the p-value with technology, using the tail or tails set by Hₐ. (Guide: Figure 1; Practice Q5, Q6)
- I can bound a p-value with a t-table and the conservative df. (Guide: Worked example 1, Check; Practice Q5)
- I can state the range in which the degrees of freedom must lie. (Practice Q4)
Reasoning
- I can interpret a p-value in context, including the observed difference and the direction of Hₐ. (Guide: Worked examples 1 and 2; Practice Q2, Q5)
- I can compare the p-value with α and write a conclusion about Hₐ, in context, with non-definitive language. (Practice Q3, Q5, Q6)
- I can say whether a conclusion can be about cause and effect, and to whom it applies. (Guide: Worked example 1, Answer the question; Practice Q6)
- I can explain how a two-sided test and a confidence interval for μ₁ − μ₂ agree. (Guide: Worked example 2, Check; Practice Q7)
All ticked? Move on to Topic 5.1, Graphical Representations Between Two Quantitative Variables, or return to the course roadmap.