The **Correlation Report** applet allows users to measure how closely survey fields are related (or "correlate"). Users may select two or more variables to analyze.

## Types of correlation

When creating scatter plots of how variables relate to each other, the correlation of these variables can fall into one of three different categories: positive correlation, negative correlation, and no correlation. Correlation values are measured by the correlation coefficient **r**, also known as "rho." Correlation values range from -1 to 1; the closer the r-value is to ±1, the stronger/more likely the correlation is between the variables. Variables that have correlation values close to 0 indicate little to no correlation between the values (e.g., height and IQ should have no correlation).

**Positive correlation**: As one variable*increases*in value, so does the other. The more positively correlated two variables are, the closer their r value will be to +1. An example of this would be height and shoe size - as one's height increases, often their shoe size does as well.**Negative****correlation**: As one variable*increases*in value, the other*decreases*in value. The more negatively correlated two variables are, the closer their r value will be to -1. An example of this would be time spent studying and time spent on video games - as one's time spent studying increases, their time spend playing video games should decrease, and vice versa.**No correlation**: There is no apparent relationship between the variables, with an r value close to or equally 0...

## Creating a Correlation Report

To access the Correlation Report applet, select **Analytics > Correlation Report** from the Survey Navigation menu.

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