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The Coefficient of determination is the proportion of variability of the dependent and independent variable this statement is true.
The primary result of the regression analysis is the coefficient of determination because it indicates the percentage of variations in the dependent variable that can be accounted for by the independent variable.
The effectiveness of a statistical model in forecasting a result is indicated by the coefficient of determination [tex]R^2[/tex]. The dependent variable in the model is a representation of the result. [tex]R^2[/tex] can have a minimum value of 0 and a maximum value of 1.
Researchers frequently rely on coefficient, also referred to as R-squared (or [tex]R^2[/tex]), when performing trend analysis to determine how strong the linear relationship is between two variables.
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