The Statistics decision tree will help you choose the correct statistical test based on your research question and the meeting of statistical assumptions.

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Parametric and Non-parametric tests for comparing two or more groups Statistics: Parametric and non-parametric tests This section covers: Choosing a test Parametric tests Non-parametric tests Choosing a Test

Ordinal is second level of measurement Ordinal associated with non-parametric statistics Ordinal also known as rank-order Ordinal gives quantitative ‘order’ of variables Ordinal no indication to value of differences between positions Ordinal example economic status high Ordinal example economic status medium Ordinal example economic status low Ordinal example agreement yes may be no Ordinal refers to order in measurement Ordinal Data

Wilcoxon Signed Rank Test is a non-parametric statistical hypothesis test Wilcoxon Signed Rank Test used when comparing two related samples Wilcoxon Signed Rank Test used as an alternative to the paired Student's t-test Wilcoxon Signed Rank Test does not assume normality in data Wilcoxon Signed Rank Test used when there are two nominal variables Wilcoxon Signed Rank Test used when there are one measurement variable Wilcoxon Signed Rank Test is based on median difference scores Wilcoxon

The assumption of homogeneity of variance must be met to conduct independent samples t-test. SPSS can be used to conduct Levene's Test of Equality of Variances.

Textbook of Parametric and Nonparametric Statistics (Paperback) (Vimala Veeraraghavan)

Parametric and Nonparametric Inference for Statistical Dynamic Shape Analysis With Applications