Briefly explain what the coefficient of determination is, and how it can be used in linear regression to assess the fit of the estimated regression equation.

 

The coefficient of determination is the variation in the dependent variable that can be explained by the independent variable(s). The higher the coefficient of determination, the better fit we have for the regression model

Step-by-step explanation

• The coefficient of determination also known as R-square is the square of the correlation coefficient. It depicts the variation in the dependent variable that can be explained by the independent variable(s)
• In regression we use it to know how much of the variation in y is explained by x. For example, suppose the coefficient of determination is 0.8. It means that 80% of the variation in the dependent variable (y) is explained by the variation in the dependent variable(s).
• The higher the coefficient of determination, the better fit we have for the regression model