Hypothesis Testing

1. Hypothesis Testing and Errors

• Null Hypothesis ($H_0$): Asserting that there is no significant difference or effect.
• Type I Error ($\alpha$): Rejecting the null hypothesis when it is actually true.
• Type II Error ($\beta$): Failing to reject the null hypothesis when it is actually false.

2. Statistical Tests

• Parametric: t-test (comparing two means), z-test (large samples), ANOVA (comparing three or more means).
• Non-Parametric: Chi-Square test (association), Kruskal-Wallis (medians).