Mann-Whitney test
The Mann-Whitney test, also known as the Wilcoxon rank-sum test, is a nonparametric statistical test used to compare the median of two independent samples. It is often used when the data is not normally distributed or when the sample sizes are small.
The Mann-Whitney test works by ranking the values in each sample, summing the ranks, and then comparing the sums to determine if there is a statistically significant difference between the two samples. The test calculates a p-value, which represents the probability that the difference between the two samples could have occurred by chance. A p-value below a certain threshold (typically 0.05) indicates that the difference is statistically significant and not likely due to random chance.
The Mann-Whitney test is a useful tool for comparing the medians of two independent samples and can provide valuable insights when working with non-normal data or small sample sizes.
When to use Mann Whitney Test?
The Mann-Whitney test, also known as the Wilcoxon rank-sum test, is a nonparametric statistical test used to compare the median of two independent samples. It is often used in situations where the data is not normally distributed or the sample sizes are small.
There are a few key scenarios when the Mann-Whitney test is particularly useful:
When the data is not normally distributed: Because the Mann-Whitney test is a nonparametric test, it does not assume normality of the data and can be used with data that is not normally distributed.
When the sample sizes are small: The Mann-Whitney test is particularly useful when the sample sizes are small, as it has good power even with small samples.
When the data are ordinal or ranked: The Mann-Whitney test is designed to work with ordinal or ranked data, so it is well-suited for data that can be easily ranked.
Overall, the Mann-Whitney test is a useful tool for comparing the medians of two independent samples, particularly when the data is not normally distributed or the sample sizes are small.
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