Student’s t-test of difference of means is used to test the significance of the difference between two sample means. Student’s t-Test of Difference of Means can be used to compare the sample means between two independent samples or two dependent samples.
Student’s t-Test of Difference of Means is a parametric test which assumes a normal distribution. Student’s t-Test of Difference of Means is used for smaller samples (i.e. the sample size should be less than 30).
There are certain terminologies in student’s t-test of difference of means that will help in understanding it in a much better manner. These terminologies are the following:
The critical value in student’s t-test of difference of means is the value that the test statistics (which is student’s t-test of difference of means) must exceed, such that the null hypothesis gets rejected. It is very important to reject the null hypothesis.
The confidence limits in student’s t-test of difference of means are the lower and upper boundary, which means that it defines a certain range where the confidence level falls.
In SPSS, student’s t-test of difference of means can be performed by selecting “analyze” from the menu. Then from analyze, select “compare means” and from the compare means option select either “Independent Sample t-test” or “Paired Sample t-test.”
Student’s t-test of difference of means is used in dealing with the problems which are associated with the statistical inference on the comparison of two different sample means.
Assumptions
In student’s t-test of difference of means, normal distribution is being assumed for two groups. If this assumption is being violated, then student’s t-test of difference of means will become unreliable.
In student’s t-test of difference of means, variances must be homogenous in nature. If this assumption is being violated, then student’s t-test of difference of means will become unreliable.
