If the third assumption is not met, the alternative test is the Mann-Whitney U-Test, which can be run to see if there is a difference between two groups for a variable with any type of distribution. The population of each group is normally distributed.The estimated standard error is an aggregate measure of the amount of variation in both groups.Дegrees of freedom: Varies by conditions, but the basic rule of thumb for hand calculations is the smaller of n 1 вЂ“ 1 and n 2 вЂ“ 1, where n is the sample size for each group. The test statistic for a two-sample independent t-test is calculated by taking the difference in the two sample means and dividing by either the pooled or unpooled estimated standard error.

H a: The population mean of one group is greater thanВ the population mean of the other group, or Ој 1В > Ој 2 This test can also be conducted with a directional alternate hypothesis: H A: The population mean of one group does not equal the population mean of the other group, or Ој 1 в‰ Ој 2 H o: The population mean of one group equals the population mean of the other group, or Ој 1 = Ој 2

For example, we could see if the mean GPA differs between freshman and senior college students by collecting a sample of each group of students and recording their GPAs. A two-sample independent t-test can be run on sample data from a normally distributed numerical outcome variable to determine if its mean differs across two independent groups.

Independent t test in spss 16