The value chosen in Step 1 determines the confidence level of your results. It tells you the likelihood that the difference in means is NOT due to random chance. For most marketing research studies, a confidence level of 95% is used.
Confidence level is related to the level of significance (α ). A 95% Confidence level corresponds to α = .05. If the Level of significance (α) = .05, that means that there is one chance in twenty that the true population means are not significantly different.
Enter the base size (# answering the question), mean and the standard deviation obtained from the first group of respondents.
Repeat Step 2 using the base size (# answering the question), the mean and the standard deviation from the second group of respondents.
Click the calculator button to obtain the results of the test.
It is assumed that your sample represents a random sample of the relevant population and that each group to be tested is independent of the other.
It is assumed that the variances within each group is equal. If one believes that the variances are not equal, the F test for Independent Variances should be conducted prior to the t-test. If the two groups have unequal variance, the t-test for unequal variance (Welch’s test) should be run.
It is not necessary for the two groups to have the same number of respondents.
Since we are testing the null hypothesis that the two means are equal, a two-tailed test is used. One-tailed tests are possible (i.e. testing if one mean is less or greater than another) but are uncommon