Linear Regression R-Squared
Posted by Mohammad Rahhal, Last modified by Diana Alkouni on 19 August 2020 10:17 AM

Overview:
R-Squared is most often used in linear regression.  Given a set of data points, linear regression gives a formula for the line most closely matching those points.  It also gives an R-Squared value to say how well the resulting line matches the original data points.

Interpretation:
R-Squared is a statistical term saying how good one term is at predicting another.  If R-Squared is 1.0 then given the value of one term, you can perfectly predict the value of another term.  If R-Squared is 0.0, then knowing one term doesn't not help you know the other term at all.  More generally, a higher value of R-Squared means that you can better predict one term from another.

Parameters:
str Source
int Periods


See Also


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