The correct answer is C. To measure the proportion of the variance in the dependent variable explained by the independent variables.
R-squared is a statistical measure of how well a model fits a set of data. It is calculated by taking the sum of squares of the residuals (SSR) and dividing it by the total sum of squares (SST). The closer R-squared is to 1, the better the model fits the data.
R-squared can be interpreted as the proportion of the variance in the dependent variable that is explained by the independent variables. For example, if R-squared is 0.8, then 80% of the variance in the dependent variable is explained by the independent variables.
A. To calculate the standard error of the regression is incorrect. The standard error of the regression is a measure of the variability of the predicted values around the true value of the dependent variable. It is calculated by taking the square root of the variance of the residuals.
B. To determine the p-value is incorrect. The p-value is a measure of the statistical significance of the results of a regression analysis. It is calculated by taking the probability of obtaining the observed results or more extreme results if the null hypothesis were true.
D. To visualize data is incorrect. R-squared is a statistical measure, not a visualization technique.