Section 1 | Hypothesis Testing

Section 1: Hypothesis Testing

1. Define hypothesis testing
   A process to test an assumption (hypothesis) about a population using data.

2. Understand the types of hypotheses

   • Null (H₀): No effect/difference.

   • Alternative (H₁): Shows effect/difference.

3. Outline the steps in hypothesis testing

   1. State H₀ and H₁

   2. Choose significance level (α)

   3. Select test statistic

   4. Determine critical region

   5. Collect data and compute statistic

   6. Compare and conclude (reject or fail to reject H₀)

4. Formulate a null hypothesis
   A default assumption (e.g., "The medicine has no effect").

5. Formulate an alternative hypothesis
   A statement that contradicts H₀ (e.g., "The medicine improves health").

6. Select a significance level

   • Common α levels: 0.05, 0.01

   • Represents the probability of Type I error (false positive)

7. Choose an appropriate test statistic

   • Depends on data type (e.g., t-test for means, chi-square for categories)