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Non-parametric Tests

CFA® Exam Level 1, Statistics

Hypothesis Testing 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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In this Course

Course Home
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
Return to Hypothesis Testing

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