What is the value for the coefficient of determination?

What is the significance of the coefficient of determination in regression analysis?

The coefficient of determination is a statistical measure that evaluates how well a regression model fits the data. It is represented by the symbol R² and ranges between 0 and 1. The coefficient of determination indicates the percentage of variation in the dependent variable that can be explained by the independent variable(s) in the regression model.

Understanding the Coefficient of Determination

In regression analysis, the coefficient of determination is a crucial metric that quantifies the goodness of fit of a regression model. It helps in assessing the strength of the relationship between the independent and dependent variables. A higher value of the coefficient of determination suggests that the model can better explain the variability in the dependent variable using the independent variable(s).

Interpreting the Coefficient of Determination

When the coefficient of determination is 1, it implies that the regression model perfectly predicts the dependent variable based on the independent variable(s). On the other hand, a coefficient of determination of 0 indicates that the model fails to explain any variability in the dependent variable.

It is essential to consider the coefficient of determination in conjunction with other statistical measures to comprehensively evaluate the regression model's performance. While a high R² value is desirable, it is crucial to assess the statistical significance and validity of the model through additional analyses.