5:39 46: | 37% = + Z . . . Use LINIS III101 IIIat01 101 Questions 24-20. The following is output from a Linear Regression Model used to examined a students expected exam score (maximum 100%) based on hours studied. SUMMARY OUTPUT Regression Statistics Multiple R 0.925683236 R Square 0.856889453 Adjusted R Square 0.821111816 Standard Error 5.467377394 Observations 6 ANOVA df SS MS Significance F Regression 1 715.9311377715.931137723.95042067 0.008079247 Residual 4 119.568862329.89221557 Total 5 CoefficientsStandard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 66.39520958 3.976336473 16.69758332 7.537428-05 55.3551296477.43528952 55.35512964 77.4352895 Hours 5.8562874251.1966463234.8939167010.008079247 2.5338645999.178710251 2.533864599 9.17871025 24) Use the above regression output to predict a student's score if he/she studies 12 hours for the exam. A. 85.0% B. 100.0% C. 136.7% D. The model is flawed and produces result outside the range of the data. 25) Using standard measures of significance, how could one determine if the number of hours studied is a significant predictor of exam scores? A. An intercept coefficient result of greater than 50. B. A t-statistic > .05 C. A p-value of