About the Pearson Correlation Coefficient

Last update: 2021-04-16
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The Pearson Correlation Coefficient is used in the Correlation Matrix as the algorithm to display the strength of the linear dependence between two variables.

This linear correlation is a statistical measure of the linear dependence, or correlation, between two variables to render a value between +1 and -1 inclusive, representing either a positive or negative dependence.

Here is the Pearson Correlation Coefficient

The Pearson’s value is visualized in the Correlation Matrix, which depicts the correlation between two defined metrics. These metrics can be compared to one another over any countable or non-countable dimension in the dataset.

You can highlight these comparisons through contrasting colors using the color picker, or by comparing values in a text map and heat map, or both.

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