Parametric Tests

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Parametric Tests

• 1) Assumption of population normality
• 2) homogeneity of variance
• Parametric more powerful than nonparametric

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Nonparametric Tests

• Nonparametric Test (distribution free testing)
• 1) Pathological conditions are represented by
  skewed distributions
• 2) Small clinical samples and samples of
  convenience cannot be considered representatives
  of larger nominal distributions
• 3) Data measured on nominal - category labels
• ordinal - rank order of observations

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Non Parametric Parametric

• Mann-Whitney U TestRank

• Unpaired T Test

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Non Parametric Parametric

• Paired T Test

• Sign Test
• Wilcoxon Signed Ranks Test

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Non Parametric Parametric

• ANOVA F Test

• Kruskal Wallis One-Way Analysis of Variance by
  Ranks

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Non Parametric Parametric

• RM ANOVA

• Friedman Two-way Analysis of Variance by Ranks

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Chi Square X2

• Non parametric test for analyzing categorical
  data e.g. yes-no
• Frequency of occurrence
• Determines if there is a difference between the
  proportions observed within a set of categories
  and the proportions that would be expected by
  chance.

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• Assumptions
• 1) frequencies represent individual counts
• 2) Categories are exhaustive and mutually
  exclusive

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