RANK SUM TESTS Meaning and
Definition
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Rank sum tests, also known as Wilcoxon rank sum tests or Mann-Whitney U tests, are non-parametric statistical tests used to compare the distributions of two independent samples. These tests determine if there is a significant difference or shift in the location or central tendency of two populations or groups. They are appropriate when the data are ordinal or not normally distributed and when the sample sizes are small or unequal.
In a rank sum test, the individual observations from both groups are ranked together based on their values. The ranks are then used to calculate a test statistic, which is typically the sum of the ranks or the U statistic. The test statistic measures the extent to which the distributions of the two groups differ.
The test statistic is then compared to critical values from a reference distribution, typically the standard normal distribution, to determine the probability or p-value of obtaining those test results by chance alone. If the p-value is less than a predetermined significance level (e.g. 0.05), the null hypothesis of no difference between the two groups is rejected in favor of the alternative hypothesis.
Rank sum tests are versatile and can be used for a variety of research questions and study designs. They provide a robust alternative to parametric tests like t-tests or ANOVA when assumptions of normality or homogeneity of variance are violated. Rank sum tests are frequently applied in clinical trials, social sciences, economics, and other fields where make comparisons across groups is important but assumptions of traditional parametric tests might not be met.
Common Misspellings for RANK SUM TESTS
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