The Pearson correlation coefficient (also called Pearson product moment correlation coefficient) is a measure of how of related 2 sets of numerical values are. It is calculated as the ratio of the covariance and the product of their standard deviations, so it is always between +1 and -1.

- +1 means a perfect correlation
- -1 means a perfect inverse correlation
- 0 means no correlation

For example, we would expect:

- a positive correlation coefficient comparing people’s height and weight (taller people are generally heavier)
- a negative correlation coefficient comparing people’s weight and how much exercize they do (people who exercize are generally less heavy)
- a zero (or very small) correlation coefficient comparing how much exercize people do and how tall they are (how much people exercize is probably not related to how tall they are)

Easy Data Transform can easily calculate the Pearson correlation coefficients for two or more columns of numerical data using it’s **Correlate** transform. For example, calculating the Pearson correlation coefficients for weight and length variables:

See the video above for more details.

This is only one of the many transforms available in Easy Data Transform. It can also help with cleaning, filtering, blending and analysing your data. All without coding. You can download the free trial in a few clicks and try it yourself.

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