Comparing Means in R


Previously, we described the essentials of R programming and provided quick start guides for importing data into R. Additionally, we described how to compute descriptive or summary statistics and correlation analysis using R software.


This chapter contains articles describing statistical tests to use for comparing means. These tests include:

  • T-test
  • Wilcoxon test
  • ANOVA test and
  • Kruskal-Wallis test


2 Comparing one-sample mean to a standard known mean

2.1 One-sample T-test (parametric)

  • What is one-sample t-test?
  • Research questions and statistical hypotheses
  • Formula of one-sample t-test
  • Visualize your data and compute one-sample t-test in R
    • R function to compute one-sample t-test
    • Visualize your data using box plots
    • Preliminary test to check one-sample t-test assumptions
    • Compute one-sample t-test
    • Interpretation of the result


One Sample t-test

Read more: —> One-Sample T-test.

2.2 One-sample Wilcoxon test (non-parametric)

  • What’s one-sample Wilcoxon signed rank test?
  • Research questions and statistical hypotheses
  • Visualize your data and compute one-sample Wilcoxon test in R
    • R function to compute one-sample Wilcoxon test
    • Visualize your data using box plots
    • Compute one-sample Wilcoxon test


One Sample Wilcoxon test

Read more: —> One-Sample Wilcoxon Test (non-parametric).

3 Comparing the means of two independent groups

3.1 Unpaired two samples t-test (parametric)

  • What is unpaired two-samples t-test?
  • Research questions and statistical hypotheses
  • Formula of unpaired two-samples t-test
  • Visualize your data and compute unpaired two-samples t-test in R
    • R function to compute unpaired two-samples t-test
    • Visualize your data using box plots
    • Preliminary test to check independent t-test assumptions
    • Compute unpaired two-samples t-test
  • Interpretation of the result


Unpaired two-samples t-test

Read more: —> Unpaired Two Samples T-test (parametric).

3.2 Unpaired two-samples Wilcoxon test (non-parametric)

  • R function to compute Wilcoxon test
  • Visualize your data using box plots
  • Compute unpaired two-samples Wilcoxon test


Unpaired two-samples wilcoxon test

Read more: —> Unpaired Two-Samples Wilcoxon Test (non-parametric).

4 Comparing the means of paired samples

4.1 Paired samples t-test (parametric)


Paired samples t test

Read more: —> Paired Samples T-test (parametric).

4.2 Paired samples Wilcoxon test (non-parametric)


Paired samples wilcoxon test

Read more: —> Paired Samples Wilcoxon Test (non-parametric).

5 Comparing the means of more than two groups

5.1 One-way ANOVA test

An extension of independent two-samples t-test for comparing means in a situation where there are more than two groups.

  • What is one-way ANOVA test?
  • Assumptions of ANOVA test
  • How one-way ANOVA test works?
  • Visualize your data and compute one-way ANOVA in R
    • Visualize your data
    • Compute one-way ANOVA test
    • Interpret the result of one-way ANOVA tests
    • Multiple pairwise-comparison between the means of groups
      • Tukey multiple pairewise-comparisons
      • Multiple comparisons using multcomp package
      • Pairwise t-test
    • Check ANOVA assumptions: test validity?
      • Check the homogeneity of variance assumption
      • Relaxing the homogeneity of variance assumption
      • Check the normality assumption
    • Non-parametric alternative to one-way ANOVA test


One-Way ANOVA Test

Read more: —> One-Way ANOVA Test in R.

5.2 Two-Way ANOVA test

  • What is two-way ANOVA test?
  • Two-way ANOVA test hypotheses
  • Assumptions of two-way ANOVA test
  • Compute two-way ANOVA test in R: balanced designs
    • Visualize your data
    • Compute two-way ANOVA test
    • Interpret the results
    • Compute some summary statistics
    • Multiple pairwise-comparison between the means of groups
      • Tukey multiple pairewise-comparisons
      • Multiple comparisons using multcomp package
      • Pairwise t-test
    • Check ANOVA assumptions: test validity?
      • Check the homogeneity of variance assumption
    • Check the normality assumption
  • Compute two-way ANOVA test in R for unbalanced designs


Two-Way ANOVA Test

Read more: —> Two-Way ANOVA Test in R.

6 MANOVA test: Multivariate analysis of variance

  • What is MANOVA test?
  • Assumptions of MANOVA
  • Interpretation of MANOVA
  • Compute MANOVA in R


MANOVA Test

Read more: —> MANOVA Test in R: Multivariate Analysis of Variance.

7 Kruskal-Wallis test

  • What is Kruskal-Wallis test?
  • Visualize your data and compute Kruskal-Wallis test in R
    • Visualize the data using box plots
    • Compute Kruskal-Wallis test
    • Multiple pairwise-comparison between groups


Kruskal Wallis Test

Read more: —> Kruskal-Wallis Test in R (non parametric alternative to one-way ANOVA).

9 Infos

This analysis has been performed using R statistical software (ver. 3.2.4).


Enjoyed this article? I’d be very grateful if you’d help it spread by emailing it to a friend, or sharing it on Twitter, Facebook or Linked In.

Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Avez vous aimé cet article? Je vous serais très reconnaissant si vous aidiez à sa diffusion en l'envoyant par courriel à un ami ou en le partageant sur Twitter, Facebook ou Linked In.

Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!





This page has been seen 476252 times