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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

1 Sample Wilcoxon Non Parametric Hypothesis Test

Posted by Ted Hessing

1 sample Wilcoxon Non Parametric Hypothesis Test is a rank-based test and it compares the standard value with a hypothesized median.

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

1 Sample Sign Non Parametric Hypothesis Test

Posted by Ted Hessing

The 1 sample sign non parametric hypothesis test simply computes a significance test of a hypothesized median value for a single data set.

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

Friedman Non Parametric Hypothesis Test

Posted by Ted Hessing

The Friedman non parametric hypothesis test is an alternative to the one-way ANOVA with repeated measures.

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

Mood’s Median Non Parametric Hypothesis Test

Posted by Ted Hessing

Mood’s median non parametric hypothesis test compares the medians of two independent samples to determine if they are the same.

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

Kruskal–Wallis Non Parametric Hypothesis Test

Posted by Ted Hessing

The Kruskal–Wallis Non-Parametric Hypothesis Test is used when a variable does not meet the normality assumptions of one-way ANOVA

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