**Introduction. **It’s compare two different sample correlations. For example, you can compare whether a correlation in women is significantly higher or lower than in men.

**Instructions. **You only have to enter the correlation (*r*) and the sample (*n*) of each sample and press *calculate*. You will have as a result the z-score and its conversion to *p* (significance level). According to your hypothesis direction, you should choose the significance of one or two tails. If you are not clear about this, look at the significance of two tails (2-tail *p*).

**Functioning. **The method used is the transformation of the correlation (*r*) to z score through the Fisher Transformation Method. Afterwards, the two z have been compared through the formula below [F.1] (Cohen & Cohen, 1983). Then the significance level of the z-score has been found.

[F.1] Z_{o} = (z_{1} – z_{2}) / (sqrt {[1 /( N_{1} – 3)] + [1 / N_{2} – 3) ]}

### Two correlation comparator – calculator

r | n | |

Sample 1 | ||

Sample 2 | ||

Z-score |
1-tail p |
2-tail p |

**References**

Cohen, J., & Cohen, P. (1983). *Applied multiple regression/correlation analysis for the behavioral sciences*. Hillsdale, NJ: Erlbaum.