The adjusted coefficient of determination is adjusted for the:

A) number of independent variables and the sample size.
B) number of dependent variables and the sample size.
C) coefficient of correlation and the significance level.
D) number of regression parameters including the y-intercept.

The adjusted coefficient of determination takes into account the number of independent variables and the sample size to provide a more accurate measure of the quality of the regression model than the ordinary coefficient of determination. It penalizes the inclusion of unnecessary independent variables in the model and adjusts for the decrease in the error sum of squares as the number of independent variables increases, which can lead to an inflated R-squared value.