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Guidelines for Selecting the Appropriate Hypothesis Test

This chapter provides a comprehensive guide for selecting the right hypothesis test based on data characteristics. It distinguishes between qualitative and quantitative data, explores the implications of the number of groups (one, two, or three), and considers whether observations are paired or repeated. The chapter outlines suitable statistical tests, including the chi-square tests, t-tests, ANOVA, and non-parametric alternatives like Mann-Whitney and Kruskal-Wallis tests. This guideline helps researchers make informed choices for accurate data analysis.

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Guidelines for Selecting the Appropriate Hypothesis Test

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  1. Chapter 21 Which test to use?

  2. Guidelines for selecting the appropriate hypothesis test (1) Type of Data (Are observations numbers?) NO Qualitative Yes Quantitative [Are observations cross-classified?] NO Yes Number of Groups One Two Three One-Variable χ2 Test Two-Variable χ2 Test t for one sample Next page

  3. Guidelines for selecting the appropriate hypothesis test (2) Number of Groups One Two Three [Are multiple observations made for same subject?] NO YES TWO GROUPS [Are quantitative observations paired?] NO YES Independent Related Samples Samples F for ANOVA [Are quantitative observation classified for two factors?] NO YES Repeated- measures F-Test One-Factor F-Test* Two-Factor F-Test t for two independent samples* Next page

  4. Guidelines for selecting the appropriate hypothesis test (3) [Are paired observations evaluated for a relationship?] NO YES (Difference) (Relationship) t for two related samples* t for a correlation coefficient [*If any assumption is seriously violated or original observations are ranks…] Mann-Whitney U-Test Wilcoxon T-Test Kruskal-Wallis H-Test

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