Stats.Blue

# Wilcoxon Rank Sum Test

• The Wilcoxon Rank Sum Test assumes that both our samples are independent SRSs and will give trustworthy conclusions only if this condition is met.

• The Wilcoxon Rank Sum Test assumes that your data come from a continuous distribution.

• The Wilcoxon Rank Sum Test is an alternative to the two-sample $t$-test when the guidelines for its use are not met (such as when the data is strongly skewed or has outliers).

 Sample 1 Sample 2 Sample data goes here (enter numbers in columns): Null Hypothesis: $H_0:$ Sample 1 and Sample 2 come from the same distribution. Alternative Hypothesis: $H_a$: Sample 1 has distribution with larger smaller different values than Sample 2. Level of Significance: $\alpha=$ 0.25 0.20 0.15 0.10 0.05 0.025 0.02 0.01 0.005 0.0025 0.001 0.0005

 Sample Sizes: $n_1=$ $n_2=$ Sample Medians: $M_1=$ $M_2=$ $W$ statistic: $W=$ Mean of $W$ under $H_0$: $\mu_W=$ Standard Deviation of $W$ under $H_0$ (with tie correction): $\sigma_W=$ $z$ Value for Test (with continuity correction): $z=$ Critical $z$ Value: $z^{*}=$ $p$-value: $p=$