Hypothesis Testing Checklist: Ensuring Accuracy in Your Calculations

Check our other pages :

Frequently Asked Questions

Define the null and alternative hypotheses clearly. This ensures you know what youre trying to prove or disprove.
Hypothesis tests rely on certain assumptions about the data. If these assumptions are violated, the results of the test may be invalid.
Select the appropriate test based on the type of data (continuous, categorical), the number of samples, and the research question. Common tests include t-tests, z-tests, and chi-square tests.
The p-value indicates the probability of observing the data (or more extreme data) if the null hypothesis is true. A small p-value (typically ≤ 0.05) suggests evidence against the null hypothesis.
Based on the p-value and significance level, either reject or fail to reject the null hypothesis. State your conclusion in the context of the original problem.
Consider using non-parametric tests, transforming the data, or collecting more data to satisfy the assumptions. Consult your H2 Math tutor for guidance.