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.