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  • https://stats.libretexts.org/Courses/Cerritos_College/Introduction_to_Statistics_with_R/12%3A_Comparing_Several_Means_(One-way_ANOVA)/12.11%3A_Removing_the_Normality_Assumption
    So, if the null hypothesis is true and there are no true group differences at all, you’d expect the between group rank sums RSS b to be very small, much smaller than the total rank sums RSS tot . Qual...So, if the null hypothesis is true and there are no true group differences at all, you’d expect the between group rank sums RSS b to be very small, much smaller than the total rank sums RSS tot . Qualitatively this is very much the same as what we found when we went about constructing the ANOVA F-statistic; but for technical reasons the Kruskal-Wallis test statistic, usually denoted K, is constructed in a slightly different way:
  • https://stats.libretexts.org/Workbench/Learning_Statistics_with_SPSS_-_A_Tutorial_for_Psychology_Students_and_Other_Beginners/11%3A_Comparing_Several_Means_(One-way_ANOVA)/11.10%3A_Removing_the_Normality_Assumption
    So, if the null hypothesis is true and there are no true group differences at all, you’d expect the between group rank sums RSS b to be very small, much smaller than the total rank sums RSS tot . Qual...So, if the null hypothesis is true and there are no true group differences at all, you’d expect the between group rank sums RSS b to be very small, much smaller than the total rank sums RSS tot . Qualitatively this is very much the same as what we found when we went about constructing the ANOVA F-statistic; but for technical reasons the Kruskal-Wallis test statistic, usually denoted K, is constructed in a slightly different way:

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