This calculator runs a two-sample \(t\) test of dependent means for given sample data sets and specified null and alternative hypotheses. Enter the data in the text area to the left. The data must be formatted with two score for each row. Each row must contain two scores that are paired together (e.g., husband-wife or first measurement and second measurement from the same subject). Alternatively, enter the sample size, the difference of sample means, and the standard deviation of the difference scores in the fields below.

Enter a value for the null hypothesis. This value should indicate the absence of an effect in your data. Indicate whether your alternative hypothesis involves one-tail or two-tails. If it is a one-tailed test, then you need to indicate whether it is a positive (right tail) test or a negative (left tail) test.

Enter an \(\alpha\) value for the hypothesis test. This is the Type I error rate for your hypothesis test. It also determines the confidence level \(100 \times (1-\alpha)\) for a confidence interval.

Press the Run Test button and a table summarizing the computations and conclusions will appear below.

Enter data:
Sample size (number of pairs) \(n=\)
Difference of sample means \({\overline X}_1 - {\overline X}_2 =\)
Standard deviation of difference scores \(s =\)
Specify hypotheses:
\(H_0: \mu_1 - \mu_2=\)
\(H_a:\)
\(\alpha=\)
Test summary
Null hypothesis \(H_0:\mu_1 - \mu_2=\)
Alternative hypothesis \(H_a: \mu_1 - \mu_2 \)
Type I error rate \(\alpha=\)
Sample size \(n=\)
Sample mean 1 \(\overline{X}_1=\)
Sample standard deviation 1 \(s_1=\)
Sample mean 2 \(\overline{X}_2=\)
Sample standard deviation 2 \(s_2=\)
Correlation between scores \(r=\)
Difference of sample means \(\overline{X}_1 - \overline{X}_2=\)
Difference scores standard deviation \(s_d=\)
Sample standard error \(s_{\overline d}=\)
Test statistic \(t=\)
Degrees of freedom \(df=\)
\(p\) value \(p=\)
Decision
Confidence interval critical value \(t_{cv}=\)
Confidence interval CI95=