Sam

Cramming Sam's top tips from chapter 7

Click on the topic to read Sam's tips from the book

Mann-Whitney test

  • The Mann–Whitney test and Wilcoxon rank-sum test compare two conditions when different participants take part in each condition and the resulting data have unusual cases or violate any assumption in Chapter 6.
  • Look at the row labelled Asymptotic Sig. or Exact Sig. (if your sample is small). If the value is less than 0.05 then the two groups are significantly different.
  • The values of the mean ranks tell you how the groups differ (the group with the highest scores will have the highest mean rank).
  • Report the U-statistic (or Ws if you prefer), the corresponding z and the significance value. Also report the medians and their corresponding ranges (or draw a boxplot).
  • Calculate the effect size and report this too.

Wilcoxon signed-rank test 

  • The Wilcoxon signed-rank test compares two conditions when the scores are related (e.g., scores come from the same participants) and the resulting data have unusual cases or violate any assumption in Chapter 6.
  • Look at the row labelled Asymptotic Sig. (2-sided test). If the value is less than 0.05 then the two conditions are significantly different.
  • Look at the histogram and numbers of positive or negative differences to tell you how the groups differ (the greater number of differences in a particular direction tells you the direction of the result).
  • Report the T-statistic, the corresponding z, the exact significance value and an effect size. Also report the medians and their corresponding ranges (or draw a boxplot).

Kruskal–Wallis test 

  • The Kruskal–Wallis test compares several conditions when different participants take part in each condition and the resulting data have unusual cases or violate any assumption in Chapter 6.
  • Look at the row labelled Asymptotic Sig. A value less than 0.05 is typically taken to mean that the groups are significantly different.
  • Pairwise comparisons compare all possible pairs of groups with a p-value that is corrected so that the error rate across all tests remains at 5%.
  • If you predict that the medians will increase or decrease across your groups in a specific order then test this with the Jonckheere–Terpstra test.
  • Report the H-statistic, the degrees of freedom and the significance value for the main analysis. For any follow-up tests, report an effect size, the corresponding z and the significance value. Also report the medians and their corresponding ranges (or draw a boxplot).

Friedman's ANOVA

  • Friedman’s ANOVA compares several conditions when the data are related (usually because the same participants take part in each condition) and the resulting data have unusual cases or violate any assumption in Chapter 6.
  • Look at the row labelled Asymptotic Sig. If the value is less than 0.05 then typically people conclude that the conditions are significantly different.
  • You can follow up the main analysis with pairwise comparisons. These tests compare all possible pairs of conditions using a p-value that is adjusted such that the overall Type I error rate remains at 5%.
  • Report the χ2 statistic, the degrees of freedom and the significance value for the main analysis. For any follow-up tests, report an effect size, the corresponding z and the significance value.
  • Report the medians and their ranges (or draw a boxplot).