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Test Types Overview
- One-Sample t-Test: Compare sample mean to known value
- Two-Sample t-Test: Compare means of two independent groups
- Paired t-Test: Compare matched pairs or before/after measurements
- Chi-Square: Test independence in categorical data
- ANOVA: Compare means across multiple groups
Interpreting Results
- p-value < α: Reject null hypothesis (significant result)
- p-value ≥ α: Fail to reject null hypothesis (not significant)
- Test Statistic: Measure of how far sample is from null hypothesis
- Degrees of Freedom: Used to determine critical values