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Non- Parametric statistics

Non-Parametric tests like Chi-Square, Mann-Whitney U-test, and Kruskal-Wallis test are used to answer research questions on relationships between variables or group differences. They are distribution-free and suitable for skewed data. Learn about their assumptions and application in analyzing categorical variables.

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Non- Parametric statistics

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  1. Non- Parametric statistics Chi-Square Mann-Whitney U-test Kruskal Wallis test

  2. Used to answer research questions ranging from whether a relationship exists between 2 variables to groups differences on an outcome measure • NPar. Tests assume distribution free

  3. Parametric: Assume normally distributed population Powerful Flexible Study effects of many independents*dep. Study the interaction between variables Shows: magnitude of significance, relationship, and direction. Non-Parametric: Distribution free Small samples Data skewed Unable to handle multivariate questions Parametric Vs Non Parametric statisticsNO CLEAR RULES WHEN ONE APPROACH PREFFERED

  4. Assumptions of Non-Parametric statistics • Frequency data • Adequate sample, at least sample size of (5) subjects • Measure independent of each other (no subject can be in more than one cell in the design, and no subject can be used more than once). • Basic theoretical structure of categorical variables remains (rationale of categorization).

  5. Examples of NP statistics Chi-Square test (x²)

  6. Chi-Square test (x²) • The impact of gender on Pressure Ulcer (PU) development . • The researcher studied whether PU incidence was different between males and females. • Hypothesis (H¹) : There is significant statistical difference in PU incidence between males and females. • H° : There is no significant statistical difference in PU incidence between males and females.

  7. Chi-Square test (x²) • On access of PU saved data set,

  8. Chi-Square test (x²) • Df (degrees of freedom): the extent to which values are free to vary in a given specific number of subjects and a total score

  9. Examples of NP statistics Mann-Whitney U test

  10. According PU data set, Age * incidence

  11. Examples of NP statistics Kruskal Wallis test

  12. According PU data set, age * group of patients

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