BACHELOR OF BUSINESS ADMINISTRATION

Detailed explanation-1: -A measure of the goodness of fit of the estimated regression equation. It can be interpreted as the proportion of the variability in the dependent variable y that is explained by the estimated regression equation. The interval estimate of the mean value of y for a given value of x.

Detailed explanation-2: -Goodness of fit for the regression is indicated by the mean square weighted deviates (MSWD), which is a measure of data point displacement from the regression line beyond each point’s analytical uncertainty.

Detailed explanation-3: -R-squared is a goodness-of-fit measure for linear regression models. This statistic indicates the percentage of the variance in the dependent variable that the independent variables explain collectively.

Detailed explanation-4: -“Goodness of Fit” of a linear regression model attempts to get at the perhaps sur-prisingly tricky issue of how well a model fits a given set of data, or how well it will predict a future set of observations.

Detailed explanation-5: -R2 is a measure of the goodness of fit of a model. In regression, the R2 coefficient of determination is a statistical measure of how well the regression predictions approximate the real data points. An R2 of 1 indicates that the regression predictions perfectly fit the data.