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Statistical Analysis Toolbox for Research: Comprehensive Guide

Discover the ideal statistical tools for your research needs including the number of dependent variables, outcome types, predictors, parametric assumptions, and analysis tools. Learn which tests to use based on your data and variables.

ivy-michael
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Statistical Analysis Toolbox for Research: Comprehensive Guide

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  1. Which Statistical Tool Do I Use?

  2. How Many Dependent Variables? What Type Of Outcome? How Many Predictors? If Categorical Predictor, Same Participants or Different in each category? Does Data Meet Parametric Assumptions? What type Of predictors? If Categorical Predictor, How many Categories? ANALYSIS TOOL Yes Independent T-test Different No Mann-Whitney Test Two Yes Paired T-test Same No Wilcoxon Rank Sum Categorical Yes One Way ANOVA Different No Kruskall Wallis Test Three + One Yes Repeated Measures ANOVA Same No Friedman’s ANOVA Yes Pearson Correlation or Regression Continuous Yes No Spearman Correlation or Kendall’s Tau Continuous Yes Ind. Factorial ANOVA or Regression Different Categorical Same No Factorial Repeated Measures ANOVA Yes Factorial Mixed ANOVA Both One Continuous Yes Multiple Regression Two + Both Yes Multiple Regression/ANCOVA Categorical Different Pearson Chi-Square or Likelihood Ratio One Continuous Logistic Regression Categorical Categorical Different Loglinear Analysis Two + Continuous Logistic Regression/Discriminant Both Different One Categorical Yes MANOVA Two + Continuous Categorical Yes Factorial MANOVA Two + Both Yes MANCOVA

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