Can Mann-Whitney U test be used with ratio data?
Can Mann-Whitney U test be used with ratio data?
My understanding was that the Mann-Whitney U is appropriate only under the following circumstances: (a) if the dependent variables are ordinal, rather than interval or ratio; (b) if the dependent variable is not normally distributed; or (c) if the data for the two groups have very unequal variances.
Which type of data is Mann-Whitney U test best to be used?
It is a non-parametric test that is used to compare two sample means that come from the same population, and used to test whether two sample means are equal or not. Usually, the Mann-Whitney U test is used when the data is ordinal or when the assumptions of the t-test are not met.
What is the test statistic for the Mann-Whitney test?
The test statistic for the Mann Whitney U Test is denoted U and is the smaller of U1 and U2, defined below. where R1 = sum of the ranks for group 1 and R2 = sum of the ranks for group 2. For this example, In our example, U=3.
How do you interpret the results of Mann-Whitney U test?
When computing U, the number of comparisons equals the product of the number of values in group A times the number of values in group B. If the null hypothesis is true, then the value of U should be about half that value. If the value of U is much smaller than that, the P value will be small.
What is a Mann-Whitney U test used for?
The Mann-Whitney U test is used to compare whether there is a difference in the dependent variable for two independent groups. It compares whether the distribution of the dependent variable is the same for the two groups and therefore from the same population.
Why use Mann-Whitney U test instead of t-test?
If your data is following non-normal distribution, then you must go for Mann whitney U test instead of independent t test. It depends on what kind of hypothesis you want to test. If you want to test the mean difference, then use the t-test; if you want to test stochastic equivalence, then use the U-test.
Is Mann-Whitney U test correlation?
A method of reporting the effect size for the Mann–Whitney U test is with a measure of rank correlation known as the rank-biserial correlation.
Can you use Mann-Whitney for large samples?
There are two versions of the Mann-Whitney U test, one for small samples (i.e., when n < 20 for each group) and one for large samples.
How do you report Mann-Whitney U test results in a table?
Reporting Mann-Whitney U Test in SPSS
- From the SPSS menu choose Analyze – Nonparametric tests – 2 independent samples.
- A new window will open.
- In the new window, we should define groups.
- We will return to the previous window.
- The results will appear in the output window.
How do you interpret Mann-Whitney results in SPSS?
The Mann-Whitney test basically replaces all scores with their rank numbers: 1, 2, 3 through 18 for 18 cases. Higher scores get higher rank numbers. If our grouping variable (gender) doesn’t affect our ratings, then the mean ranks should be roughly equal for men and women.
What is effect size in Mann-Whitney U test?
Mann-Whitney-U-Test Effect Size In general, one can say about the effect strength: Effect Size r less than 0.3 -> small effect. Effect Size r between 0.3 and 0.5 -> medium effect. Effect Size r greater than 0.5 -> large effect.
Which statistical test should I use?
What type of statistical test to use?
|Tukey-Kramer test||1||after a significant one-way anova, test for significant differences between all pairs of groups|
|Bartlett’s test||1||test the hypothesis that the standard deviation of a measurement variable is the same in different groups|
Why choose Mann-Whitney U test?
Does Mann-Whitney require equal sample sizes?
Yes, the Mann-Whitney test works fine with unequal sample sizes.
When to use Mann-Whitney U test in SPSS?
The Mann-Whitney U test is used to compare differences between two independent groups when the dependent variable is either ordinal or continuous, but not normally distributed.
What statistical test would be used with interval or ratio data?
Discriminant analysis is used when you have one or more normally distributed interval independent variables and a categorical dependent variable.
How do you compare two sets of data statistically?
When you compare two or more data sets, focus on four features:
- Center. Graphically, the center of a distribution is the point where about half of the observations are on either side.
- Spread. The spread of a distribution refers to the variability of the data.
- Unusual features.
Does Mann Whitney assume equal variance?
So, Mann-Whitney U test assumes the equal variances (homoscedasticity) and the different variations of two populations affect results of the test.
What are the assumptions of the Mann-Whitney U test?
Assumptions for the Mann Whitney U Test
- The dependent variable should be measured on an ordinal scale or a continuous scale.
- The independent variable should be two independent, categorical groups.
- Observations should be independent.
- Observations are not normally distributed.
How do you interpret Mann Whitney results in SPSS?