Overview
This lecture reviews how to write statistical hypothesis test conclusions, focusing on a population mean (average) t-test example and interpreting results.
Writing Conclusions for Hypothesis Tests
- If the null hypothesis is also the claim, rejecting the null means rejecting the claim.
- State that there is significant evidence to reject the claim if the test result is significant.
- Example: "There is significant evidence to reject the claim that the population mean amount spent is $11."
- Rejecting the claim implies the data strongly disagree with it.
- The sample data may also suggest, for example, the mean is significantly higher than $11.
Steps in a Population Mean t-Test
- Perform the t-test to assess if sample data supports or rejects the claimed mean.
- Interpreting results requires connecting the statistical outcome to a real-world claim.
- Drawing correct conclusions follows a structured format as shown in previous lessons.
Key Terms & Definitions
- Null Hypothesis (H₀) — The default assumption or claim being tested, often representing no effect or status quo.
- t-Test — A statistical test used to compare a sample mean to a population mean when population standard deviation is unknown.
- Significant Evidence — Statistical result strong enough to reject the null hypothesis at a chosen significance level.
Action Items / Next Steps
- Review the conclusion-writing table or guide from the previous video.
- Practice writing formal conclusions for hypothesis tests.
- Prepare for upcoming lessons on more hypothesis testing examples.