RegressionR2

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This function isn't compatible with all data platform connections. To check if your connection supports it, see Supported data platforms and feature compatibility.

The RegressionR2 function calculates the R² value, or coefficient of determination, of the linear regression line. This value is a goodness-of-fit measure, and explains how well the independent variable explains variations in the dependent variable.

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The RegressionR2 function is an aggregate function.
Aggregate functions evaluate one or more rows of data and return a single value.

In a table element, the aggregate is calculated for each grouping. For information on how to add a grouping with an aggregate calculation to a table, see Group columns in a table.

In a table with no groupings, the aggregate is calculated for each row. For information on how to calculate summary statistics across all rows in a table, see Add summary statistics to a table.

To learn more about using aggregate functions, see Building complex formulas with grouped data.

Syntax

RegressionR2(y, x)

Function arguments


y	The dependent variable, expected to change as a result of changes in `x`.
x	The independent variable.

Notes

The function returns null if the arguments used provide only a single data point.

Example

A table contains an AdSpend column (tracking monthly advertising spend) and a Revenue column (tracking month revenue). You can use the RegressionR2 function to calculate how well advertising spend explains variations in revenue.

RegressionR2([Revenue], [AdSpend])

Possible output values range from 0 (no correlation) to 1 (perfect correlation), representing a percentage from 0 to 100. If the output is 0.4, for example, 40% of the variation in revenue can be explained by changes in advertising spend.