Which of the Following Best Describes the Residuals in Regression

Which of the following best describes the residuals in regression analysis? $\begin{array}{|l|l|}\hline\text { A. } & \text {The residuals are the difference between \( \mathrm{x} \) data values observed }\\& \text {and \( \mathrm{x} \) predicted model values. } \\\hline \text { B. } & \text {The residuals are the difference between the actual slope and the predicted model slope. } \\\hline \text { C. } &\text {The residuals are the difference between the \( y \) data values observed }\\& \text {and the predicted \( y \) model values. } \\\hline \text { D. } &\text {The residuals are the addition of the \( \mathrm{y} \) data values observed and predicted model values. }\\\hline\end{array}$