Hypothesis Testing

13 lessons0%

Lessons

What is Hypothesis Testing

Test Statistic, Type I and type II Errors, and Significance Level

Decision Rule in Hypothesis Testing

p-Value in Hypothesis Testing

Selecting the Appropriate Test Statistic

Hypothesis Testing with t-statistic

Hypothesis Testing with z-statistic

Tests Concerning Differences in Means

Paired Comparision Tests - Mean Differences When Populations are Not Independent

Hypothesis Tests Concerning Variances

Chi-square Test – Test for value of a single population variance

F-test - Test for the Differences Between Two Population Variances

Non-parametric Tests

Quizzes

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F-test - Test for the Differences Between Two Population Variances

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Non-parametric Tests

In parametric tests we make assumptions about the distribution of the population and each parametric test is specific to a population parameter such as mean or variance, for example, a z-test.

A nonparametric test is not concerned with a parameter or makes minimal assumptions about the population being sampled.

A nonparametric test is primarily used in three situations:

when data does not meet distributional assumptions
when data are given in ranks
when the hypothesis we are addressing does not concern a parameter