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Lesson 13 of 13

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

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Hypothesis Testing

13 lessons

Lessons

1
What is Hypothesis Testing
2
Test Statistic, Type I and type II Errors, and Significance Level
3
Decision Rule in Hypothesis Testing
4
p-Value in Hypothesis Testing
5
Selecting the Appropriate Test Statistic
6
Hypothesis Testing with t-statistic
7
Hypothesis Testing with z-statistic
8
Tests Concerning Differences in Means
9
Paired Comparision Tests - Mean Differences When Populations are Not Independent
10
Hypothesis Tests Concerning Variances
11
Chi-square Test – Test for value of a single population variance
12
F-test - Test for the Differences Between Two Population Variances
13
Non-parametric Tests

Quizzes

Hypothesis Testing
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