Enter raw data that is formatted as described on the right:
This calculator runs a two sample test for the difference of independent correlations test for a given sample data set and specified null and alternative hypotheses. Enter the data in the text area to the left. The data must be formatted with a label that identifies the condition (group) and one pair of scores for each row. The data on each row must be separated by a space, tab, or comma. Alternatively, below the text area, you can enter the sample correlations and sample size values.

Enter a value for the null hypothesis. This value should indicate the absence of an effect in your data. If you want to test for a difference of correlations, the value should be zero. The null value must be between \(-2\) and \(+2\). If you enter a value other than zero, you will be prompted to enter the null population proportions in additional text fields.

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.

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

Contrary to other hypothesis testing calculators in this textbook, this program does not compute a confidence interval for the difference of correlations. While a confidence interval can be generated, in principle, the calculations involve concepts beyond the coverage this textbook.

Or enter sample information:
Sample correlation for group 1, \(r_1=\)
Sample size for group 1, \(n_1=\)
Sample correlation for group 2, \(r_2=\)
Sample size for group 2, \(n_2=\)
Specify hypotheses:
\(H_0: \rho_1 - \rho_2=\)
\( \rho_1=\) \( \rho_2=\)
\(H_a:\)
\(\alpha=\)
Test summary
Null hypothesis \(H_0: \rho_1 - \rho_2=\)
Difference of null Fisher \(z\) transforms \(z_{\rho_1} - z_{\rho_2}=\)
Alternative hypothesis \(H_a: \rho_1 - \rho_2 \)
Type I error rate \(\alpha=\)
Label for group 1
Sample size for group 1\(n_1=\)
Sample correlation for group 1 \(r_1=\)
Fisher \(z\) transform of \(r_1\) \(z_{r_1}=\)
Label for group 2
Sample size for group 2\(n_2=\)
Sample correlation for group 2 \(r_2=\)
Fisher \(z\) transform of \(r_2\) \(z_{r_2}=\)
Sample standard error \(s_{z_{r_1}-z_{r_2}}=\)
Test statistic \(z=\)
\(p\) value \(p=\)
Decision