Introduction to Hypothesis Testing

INTRODUCTION TO HYPOTHESIS TESTING

• Definition: Hypothesis testing is a statistical method that uses sample data to evaluate a hypothesis about a population.

• Purpose: The goal is to determine whether there is enough evidence to support a specific claim.

• Key Terms:

  • Null Hypothesis (H_0): The hypothesis that there is no effect or no difference, serving as a default position.

  • Alternative Hypothesis (H_a): The hypothesis that indicates the presence of an effect or a difference.

• Process Overview:

  1. State the null and alternative hypotheses.

  2. Choose a significance level (theta), usually set at 0.05.

  3. Collect data and calculate a test statistic.

  4. Determine the p-value or critical value.

  5. Make a decision to reject or fail to reject H_0.

• Types of Errors:

  • Type I Error: Rejecting H_0 when it is true.

  • Type II Error: Failing to reject H_0 when it is false.