Respuesta :
The proportion of the variation in the dependent variable y that is explained by the estimated regression equation is measured by the coefficient of determination.
What is coefficient of determination?
The effectiveness of a statistical model in forecasting a result is shown by the coefficient of determination (R²). The dependent variable in the model is a representation of the result.
R² can have a value of 0 or 1, with 1 being the maximum achievable. Simply said, a model's R² will be closer to 1 the more accurate its predictions are.
R² is a more precise measure of goodness of fit. The amount of volatility in the dependent variable that the model can account for.
You can typically tell whether your linear regression data's R² is high or low by graphing it. The graphs below, for instance, display two sets of simulated data:
Dots represent the observations.
The line of best fit, or predictions of the model, is displayed as a black line.
Purple lines represent the deviations (the residuals) between the data and their expected values.
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