# Data considerations for Mann-Whitney Test

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

The populations of each sample must have the same shape and spread

If the populations have different shapes or spreads, use 2-Sample t without pooling variances.

The data do not need to be normally distributed

However, if you have more than 15 observations in each sample or your data aren't severely skewed, use 2-Sample t because the test has more power.

The sample data should be selected randomly

In statistics, random samples are used to make generalizations, or inferences, about a population. If your data are not collected randomly, your results may not represent the population. For more information, go to Randomness in samples of data.

Each observation should be independent from all other observations
The independence of observations is determined by whether one observation provides information about another observation, as follows:
• If an observation provides no information about the value of another observation, the observations are independent.
• If an observation provides information about another observation, the observations are dependent. If your observations are dependent, your results may not be valid.