Comparison of correlation coefficients

The test for checking the equality of the Pearson product-moment correlation coefficients, which come from 2 independent populations

This test is used to verify the hypothesis determining the equality of 2 Pearson's linear correlation coefficients ($R_{p_1}$, $R_{p_2})$.

Basic assumptions:

Hypotheses:

\begin{array}{cl}
\mathcal{H}_0: & R_{p_1} = R_{p_2}, \\
\mathcal{H}_1: & R_{p_1} \ne R_{p_2}.
\end{array}

The test statistic is defined by:

\begin{displaymath}
t=\frac{z_{r_{p_1}}-z_{r_{p_2}}}{\sqrt{\frac{1}{n_1-3}+\frac{1}{n_2-3}}},
\end{displaymath}

where:

$\displaystyle z_{r_{p_1}}=\frac{1}{2}\ln\left(\frac{1+r_{p_1}}{1-r_{p_1}}\right)$,

$\displaystyle z_{r_{p_2}}=\frac{1}{2}\ln\left(\frac{1+r_{p_2}}{1-r_{p_2}}\right)$.

The test statistic has the t-Student distribution with $n_1+n_2-4$ degrees of freedom.

The p-value, designated on the basis of the test statistic, is compared with the significance level $\alpha$:

\begin{array}{ccl}
$ if $ p \le \alpha & \Longrightarrow & $ reject $ \mathcal{H}_0 $ and accept $ 	\mathcal{H}_1, \\
$ if $ p > \alpha & \Longrightarrow & $ there is no reason to reject $ \mathcal{H}_0. \\
\end{array}

Note

A comparison of the slope coefficients of the regression lines can be made in a similar way. </WRAP>