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==== Cohen's ''q'' ==== Another measure that is used with correlation differences is Cohen's q. This is the difference between two Fisher transformed Pearson regression coefficients. In symbols this is <math display="block"> q = \frac 1 2 \log \frac{ 1 + r_1 }{ 1 - r_1 } - \frac 1 2 \log \frac{1 + r_2}{1 - r_2} </math> where ''r''<sub>1</sub> and ''r''<sub>2</sub> are the regressions being compared. The expected value of ''q'' is zero and its variance is <math display="block"> \operatorname{var}(q) = \frac 1 {N_1 - 3} + \frac 1 {N_2 -3} </math> where ''N''<sub>1</sub> and ''N''<sub>2</sub> are the number of data points in the first and second regression respectively.
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