The coefficient of determination, often denoted as R, quantifies the proportion of variance in a dependent variable that is predictable from an independent variable or variables. In Excel, its calculation assesses the goodness of fit of a regression model. For instance, if a regression model predicting sales based on advertising spend yields an R of 0.85, it suggests that 85% of the variability in sales can be explained by the variation in advertising expenditure.
Understanding this statistical measure is vital for evaluating the accuracy and reliability of predictive models. A higher coefficient signifies a stronger relationship between the variables and implies a more effective model. Its application extends across diverse fields, including finance, economics, and science, enabling data-driven decision-making and informed forecasting. The development of this measure has allowed researchers to assess model fit more rigorously, moving beyond simple visual inspection of data.
