Lesson Plan

• Describe null and alternative hypotheses, significance level, and p‑value.
• Apply the correct test statistic (Z, t, or correlation‑t) to sample data.
• Compute critical values or p‑values and make a justified decision.
• Interpret the outcome of hypothesis tests for means, correlation, and regression in context.
• Check the required assumptions (normality, sample size, linearity) before testing.

• Projector with slide deck
• Whiteboard and markers
• Scientific calculators or computers with statistical software
• Handout containing formula sheet and worked example
• Worksheet with paired data for correlation and regression
• Graph paper for sketching scatter plots

Begin with a short quiz that asks students to match key terms (null hypothesis, p‑value, α) to their definitions. Review how this terminology connects to previous work on probability distributions. Explain that by the end of the lesson they will be able to choose and execute the appropriate hypothesis test and clearly communicate the result.

1. Do‑now (5'): Quick quiz on hypothesis terminology; collect answers.
2. Mini‑lecture (10'): Review the general testing procedure, significance levels, and when to use Z vs t.
3. Guided example (15'): Work through the “unknown σ” mean test (t‑test) using the provided sample data.
4. Collaborative activity (10'): In pairs, calculate Pearson r for a given data set, compute the t‑statistic, and decide on H₀.
5. Whole‑class demonstration (10'): Simple linear regression hypothesis test for the slope, including confidence interval interpretation.
6. Check for understanding (5'): Exit ticket – students write the decision rule for a chosen α and test type.

Summarise the five‑step testing framework and highlight common pitfalls such as ignoring assumptions. Collect the exit tickets to gauge individual mastery. Assign homework: complete a worksheet that includes a mean test, a correlation test, and a regression slope test, each with full justification.