Verdict Errors and Statistical Power: Understanding Type I, Type II Errors in Hypothesis Testing
Shared by A STEM Educator
Students will be able to identify Type I and Type II errors in context, explain the consequences of each error type, describe the relationship between alpha and power, and analyze how sample size, effect size, and significance level affect the power of a test.
Lesson Overview
Students use the courtroom verdict analogy to build intuition for Type I and Type II errors, then progressively connect these ideas to significance level, power, and the factors that influence power in formal hypothesis tests.
Materials
- Vertical whiteboards or chart paper
- Dry-erase markers
- Random grouping tool
- Printed task cards (optional)
- Calculators
Scaffolded Task Progression
Complete the table:
| Jury says GUILTY | Jury says NOT GUILTY | |
|---|---|---|
| Defendant is INNOCENT | ??? | ??? |
Which verdict is an error? What kind of mistake is it — and what are the real-world consequences?
| Jury says GUILTY | Jury says NOT GUILTY | |
|---|---|---|
| Defendant is INNOCENT | ??? | ??? |
| Defendant is GUILTY | ??? | ??? |
Label each cell: CORRECT DECISION or ERROR. For each error cell, write one sentence describing the real-world consequence.
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