- 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 values than Sample 2. | |

Level of Significance: | $\alpha=$ |

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: | $p=$ |