The Correlation Coefficient is often used in comparing bivariate data. Ex job satisfaction stratified by income.

correlation coefficient
correlation coefficient

The correlation coefficient varies between -1 and +1. Values approaching -1 or +1 indicate strong correlation (negative or positive) and values close to 0 indicate little or no correlation between x and y.

Sample Correlation Coefficient

Correlation does not mean causation.

A positive correlation can be either good news or bad news

A negative correlation is not necessarily bad news. It merely means that as the independent variable goes more negative, the dependent variable goes negative as well.

r = 0; does not indicate the absence of  a relationship, a curvilinear pattern may exist; r=-0.76 has the same predictive power as r = +0.76

Correlation Coefficient Videos

Graphical Analysis

Related to linear regression plots.

The pattern of dots is tighter with a strong correlation.

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