# Pearsons Product Moment Correlation Coefficient

Also known as **Product-Moment Coefficient of Correlation**, **Pearson's correlation**, **Cross-Correlation Coefficient**.

This is a parametric version of the Spearman

This is the most popular measure of correlation but it can only be used when the data has a measurement interval scale.

Defined as the covariance of the variables divided by the product of their standard deviations.

This is an example of a parametric technique ??

This method assumes that the scores are in precise numbers, rather than scales

The result obtained in meaningless if the set of scores shows any curvilinear relationship

Always plot a scattergram first to make sure the data falls into an unambigious linear pattern.

What does this tell us

The correlation coefficient measures the strength of the linear relationship between two variables

This only indicates a linear relationship, so it doesn't mean that the variables are not closely related in a non linear way.

This also has a maximum value of 1 and a minimum value of -1.

When the coefficient is positive the two variables tend to move in the same direction as each other

When the coefficient is negative the two variables tend to move in opposite directions

A correlation of 1 indicates a perfect positive linear relationship.

A correlation of -1 indicates a perfect negative linear relationship.

A correlation of 0 indicates no linear relationship.

Assumptions:

1- The relationship must be linear (always draw an xy scatter chart to check)

2- The scores must be normally distributed

3- The two data sets must have similar variances

4- They must have scores in the form of precise numbers

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