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.
- The hypothesis statement:
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Formulating the null hypothesis, formulating the alternative hypothesis, two-tailed tests, one-tailed tests.
- Level of significance:
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Probability of making a wrong decision, cost of a wrong decision.
- Decision rules:
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Rejecting null hypothesis, not rejecting null hypothesis, decision errors (type I and type II).
- Testing methods:
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Critical value method, p-value method, confidence interval method.
- Estimation:
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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.
- Conclusion:
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Making the decision, restating the hypothesis.
- 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.