This calculator is used to compare the means of two independent groups to determine if they are significantly different from one another.

Step 1

Select desired confidence level:

90 95 99  %

Step 2

Group 1 Information
Enter the sample size, mean, and standard deviation of the first group.
Enter a positive number for sample size. Enter a positive number for frequency or a number from 1-100 for percent.

 

sample size

Step 3

Group 2 Information
Enter the sample size, mean, and standard deviation of the second group.
Enter a positive number for sample size. Enter a positive number for frequency or a number from 1-100 for percent.

 

sample size

RESULTS

"T": 

Degrees of Freedom:

Actual Confidence Level:

%

Are means significantly different at the selected confidence level?

What the results mean

When you interview two independent samples, there is some likelihood (confidence level) that the means obtained from the two groups are significantly different. If the t-value obtained from this test is greater than the t distribution value for a given confidence level, the observed means are significantly different.

More information

Step 1: Confidence Level

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.

Step 2: Enter Group 1 Information

Enter the base size (# answering the question), mean and the standard deviation obtained from the first group of respondents.

Step 3: Enter Group 2 Information

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.

Assumptions

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.