Researchers often follow several rules of thumb: Note: When one or more of the assumptions for the Independent Samples t Test are not met, you may want to run the nonparametric Mann-Whitney U Test instead. The Welch t Test is also known an Unequal Variance t Test or Separate Variances t Test. This alternative statistic, called the Welch t Test statistic 1, may be used when equal variances among populations cannot be assumed. However, the Independent Samples t Test output also includes an approximate t statistic that is not based on assuming equal population variances. When this assumption is violated and the sample sizes for each group differ, the p value is not trustworthy.Homogeneity of variances (i.e., variances approximately equal across groups).Among moderate or large samples, a violation of normality may still yield accurate p values.Non-normal population distributions, especially those that are thick-tailed or heavily skewed, considerably reduce the power of the test.Normal distribution (approximately) of the dependent variable for each group.Random sample of data from the population.Violation of this assumption will yield an inaccurate p value.No subject in either group can influence subjects in the other group.Subjects in the first group cannot also be in the second group.There is no relationship between the subjects in each sample.Independent samples/groups (i.e., independence of observations).Cases that have values on both the dependent and independent variables.Independent variable that is categorical and has exactly two categories.Dependent variable that is continuous (i.e., interval or ratio level).
Your data must meet the following requirements:
0 kommentar(er)
