A Consumer Researcher Was Interested in What Factors Influence People's $\quad$

A consumer researcher was interested in what factors influence people's fear responses to horror films. She measured gender and how much a person is prone to believe in things that are not real (fantasy proneness) . Fear responses were measured too. In this table, what does the value 847.685 represent? $\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$$\quad$ ANOVA $^ { a }$
$\begin{array}{|ll|r|r|r|r|r|}\hline{\text { Model }} &&\text { Sum of } \\&&\text { Squares }& \mathrm{df} & \text { Mean Square } & {\mathrm{F}} &{\text { Sig. }} \\\hline 1 & \text { Regression } & 103.457 & 1 & 103.457 & 9.419 & .003^{b} \\& \text { Residual } & 900.675 & 82 & 10.984 & & \\& \text { Total } & 1004.132 & 83 & & & \\\hline 2 & \text { Regression } & 156.448 & 2 & 78.224 & 7.475 & .001^{\mathrm{C}} \\& \text { Residual } & 847.685 & 81 & 10.465 & & \\& \text { Total } & 1004.132 & 83 & & & \\\hline \end{array}$
a. Dependent Variable: Fear after Horror Film
b. Predictors: (Constant) , Gender
c. Predictors: (Constant) , Gender, Fantasy Proneness

A) The improvement in prediction of fear resulting from including both gender and fantasy proneness as predictors in the model
B) The improvement in prediction of fear resulting from adding fantasy proneness to the model
C) The total error in predicting fear scores when both gender and fantasy proneness are included as predictors in the model
D) The reduction in the error in predicting fear scores when fantasy proneness is added to the model