Which term refers to the squared correlation coefficient between independent and dependent variables?

R-squared, also known as the coefficient of determination, measures the proportion of the variance for a dependent variable that's explained by an independent variable or variables in a regression model. It takes the correlation coefficient and squares it, which allows it to express how well the independent variable(s) predict the dependent variable.

When the R-squared value is close to 1, it indicates a strong linear relationship, meaning that a large portion of the variation in the dependent variable can be explained by the independent variable(s). Conversely, an R-squared value near 0 suggests that the independent variable(s) do not explain much of the variation in the dependent variable.

This term is particularly useful in statistical analysis as it helps researchers and analysts assess the effectiveness of their models. Understanding R-squared is critical for evaluating model fit, which is a vital aspect of data-driven decision-making.