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Home  /  Six Sigma Study Guide Articles  /  Performing Hypothesis Tests with Non Normal Data

Category: Performing Hypothesis Tests with Non Normal Data

Ted Hessing

Mann-Whitney Hypothesis Test

Posted by Ted Hessing

Mann-Whitney Non Parametric Hypothesis Test is used to compare two sample means that come from the same population.

This entry was posted in Analyze, Performing Hypothesis Tests with Non Normal Data and tagged ASQ, Black Belt, Green Belt, IASSC, non-parametric, QuestionSet. Bookmark the permalink.
Ted Hessing

Goodness of Fit

Posted by Ted Hessing

A Chi-Square goodness of fit test tells how well a categorical (nominal or ordinal) sample distribution fit into a hypothetical distribution.

This entry was posted in Analyze, Performing Hypothesis Tests with Non Normal Data and tagged ASQ, Black Belt, Download, IASSC, Villanova. Bookmark the permalink.
Ted Hessing

Chi Square Distribution & Hypothesis Test

Posted by Ted Hessing

The chi square (χ2) distribution is the best method to test a population variance against a known or assumed value of the population variance

This entry was posted in Advanced Data Distributions, Analyze, Measure, Performing Hypothesis Tests with Non Normal Data and tagged ASQ, Black Belt, Breakup, Download, Green Belt, IASSC, QuestionSet, Villanova. Bookmark the permalink.
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