Based on your findings from the previous question, perform an appropriate directional Wilcoxon Rank- Sum Test. How are the significance results different from the directional t-test using this non-parametric test?
Using pcnt_unemployed at the outcome variable and urban as the grouping variable
What will be an ideal response?
Since we know that rural postcodes have a smaller mean than urban postcodes, we need to use the option
alternative="less" in the Wilcoxon Rank-Sum Test.
wilcox.test(pcnt_unemployed~urban, alternative="less", data=depdata)
Wilcoxon rank sum test with continuity correction
data: pcnt_unemployed by urban
W = 76650, p-value < 2.2e-16
alternative hypothesis: true location shift is less than 0
We see that p < 2.2e-16 and thus the rural postcode distribution is significantly less than the urban
postcodes. Therefore, our significance results are the same as they were with the t-test.
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