Pronunciation: [ɹˈaŋk sˈʌm tˈɛst] (IPA) 
The Rank Sum Test is a statistical method that compares the medians of two independent datasets. The spelling of the word "rank" is /ræŋk/, which is pronounced with a short "a" sound and a voiced velar fricative "ng" sound. The spelling of the word "sum" is /sʌm/, which is pronounced with a short "u" sound and a voiceless labial nasal "m" sound. Together, the phonetic transcription of "Rank Sum Test" is /ræŋk sʌm tɛst/.
Rank sum test is a statistical hypothesis test used to determine whether two independent samples have been drawn from populations with the same distribution, or alternatively, whether the distributions from which the samples have been drawn have the same median. This nonparametric test is based on the ranks of the observations rather than their actual values and is suitable for analyzing data that violates the assumptions of normality or homoscedasticity.
The rank sum test involves summing the ranks of one sample and comparing it with the sum of the ranks of the other sample. The test statistic is computed as the smaller of the two sums. Under the null hypothesis of equal distributions or medians, this test statistic follows a known distribution, typically the normal distribution or the t-distribution. By comparing the test statistic to the appropriate critical value, the researcher can determine the statistical significance of the difference between the two samples.
The rank sum test is particularly useful when dealing with ordinal or non-numerically scaled data, as it circumvents the limitations of parametric tests that require assumptions regarding the underlying distribution. It is widely employed in various fields, such as biology, psychology, and economics, where variables may have non-normal distributions or when sample sizes are small. Additionally, the rank sum test can be easily implemented in statistical software packages, making it a practical choice for researchers.
