Image of logo.

Business Smarts!

                                Max Your Grade!


Module Description

Statistics I - Hypothesis Testing





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.



Return to Subjects.