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Coefficient of Determination

The coefficient of determination (𝑹^2 ) of multiple regression is a goodness of fit measure

What is the Coefficient of Determination?

The coefficient of determination (𝑹 ^2 ) of multiple regression is a goodness of fit measure. The square of the correlation between Y and the anticipated value of Y is the coefficient of determination R^2 in multiple regression.

Example of Coefficient of Determination:

$ R^{2}\, = \, 1\, -\, \frac{RSS}{TSS} $

R2 = Coefficient of Determination
TSS = total sum of squares
RSS = sum of squares of residuals

Why is Coefficient of Determination important?

The most frequent way to analyse r-squared is to see how well the regression model matches the data. An r-squared of 60%, for example, indicates that 60% of the data fits the regression model. A greater r-squared suggests a better fit for the model in general.

Owais Siddiqui
1 min read
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