Match these non-parametric statistical tests with their parametric counterpart by putting the corresponding letter on the line. Friedman test
Kruskal-Wallis H test
Mann-Whitney U test
Wilcoxon Signed-Ranks T test
A. Paired-sample t-test.
B. Independent-sample t-test.
C. One-way ANOVA, independent samples.
D. One-way ANOVA, repeated measures.

A. Paired-sample t-test.   ---   Wilcoxon Signed-Ranks T testB. Independent-sample t-test.   ---  Mann-Whitney U testC. One-way ANOVA, independent samples.   ---   Kruskal-Wallis H testD. One-way ANOVA, repeated measures.  ---   Friedman test

Step-by-step explanation:

The nonparametric statistics is a branch of statistics, that seeks out the population distribution that is either being distributed freely or specifically.  Wilcoxon Signed-Ranks T-test is a hypothesis test used to compare the two or pre related columns that can be matched and maybe a repeated measure on a single sample.The Mann-Whitney U test is a null hypothesis and states the probability of a random sample of X and Y from the population is greater than the X and that Y is greater than X.Kruskal-Wallis H test is a test of one variance analysis and tests that sample originates from the same distribution.The  Friedman test is used to find treatment across multiple tested attempts. It involves the ranking of the rows and then considering the values of the column.

Not sure what the question is?