University of Central Florida (UCF) GEB4522 Data Driven Decision Making Practice Exam 2

The coefficient of determination, commonly represented as R-squared, quantifies the proportion of variability in the dependent variable that can be explained by the independent variable(s) in a regression model. This statistical measure provides insight into how well the regression predictions approximate the real data points. An R-squared value of 1 indicates a perfect fit, meaning all variability is accounted for by the model, while a value of 0 indicates that the model does not explain any variability.

This concept is particularly vital in assessing the effectiveness of a regression model, as it helps in evaluating how changes in the independent variable are associated with variations in the dependent variable. Understanding and interpreting R-squared assists researchers and analysts in making informed data-driven decisions, as they can assess the strength and validity of their predictive models.