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wilcox.test(data$personal_sex, data$dwelling_problems_safety, mu=0, alt="two.sided", conf.int=T, conf.level =0.95, paired=F, exact=F, na.action = na.omit)

My Hypothesis is : H0 : Male = Female H1 : Male not equal to female

So my question is when, I reject the null hypothesis and accept that the difference in male and female is there, how do I interpret the male and female difference which gender has more effect on the hypothesis?

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  • $\begingroup$ Why is the regression being used here? The Wilcoxon signed-rank test does not simply test the difference in the original variables. $\endgroup$
    – Galen
    Jan 24, 2023 at 18:23
  • $\begingroup$ Are you sure you want the wilcox.test and not the t.test? $\endgroup$
    – Onyambu
    Jan 24, 2023 at 18:48
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    $\begingroup$ Which gender has the greater effect in the data? That's your answer. $\endgroup$
    – whuber
    Jan 24, 2023 at 19:07
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    $\begingroup$ Your call to wilcox.test is not going to be doing what you want it to. $\endgroup$
    – Glen_b
    Jan 24, 2023 at 23:37

1 Answer 1

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Since the hypothesis is about the difference between males and females, it is not really possible to say that one gender had "more effect" on the hypothesis ---i.e., more effect on the difference. As an analogy, if I say there is 2.5 years difference in age between me and my brother, it would be silly to then ask which of our ages had the most effect on this age difference.

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