 Module Description

Statistics I - Hypothesis Testing

Contents

This module is aimed at students who are taking their second course in statistics and introduces students to hypothesis testing.

The following is a list of the specific topics this module covers.

1. The hypothesis statement:
Formulating the null hypothesis, formulating the alternative hypothesis, two-tailed tests, one-tailed tests.

2. Level of significance:
Probability of making a wrong decision, cost of a wrong decision.

3. Decision rules:
Rejecting null hypothesis, not rejecting null hypothesis, decision errors (type I and type II).

4. Testing methods:
Critical value method, p-value method, confidence interval method.

5. Estimation:
Computation of Z-scores, t-scores, Chi-squared scores, and F scores for one mean, one proportion, one variance, two means, two proportions, two variances, one-way analysis of variance, contingency table.

6. Conclusion:
Making the decision, restating the hypothesis.

7. Questions: 1,000 practice questions with explained solutions.

Pre-requisites for this Module

This module requires prior knowledge of samples, mean, variance, and normal probability such as that in the Introduction to Statistics module.

This module is a pre-requisite for the Statistics II module on linear regression.

Sample Module.