Please give the detailed process

You run a regression of home price on the number of bedrooms, the house size, and lot size and obtain the following output: Regression Statistics Multiple R 0.748 R Square 0.560 Adjusted R Square 0.546 Standard Error 25022.708 Observations 100 ANOVA df SS MS F Regression 3 7.65E+10 2.55E+10 40.727 Residual 96 6.01E+10 6.26E+08 Total 99 1.37E+11 Coefficients Standard Error t Stat P-value Intercept 37717.595 14176.742 2.661 .01 Bedrooms 2306.081 6994.192 0.330 .74 House Size 74.297 52.979 1.402 .16 Lot Size -4.364 17.024 -0.256 79 Fo.05,3,96 = 2.699 Fo.05,4,96 = 2.466 Fo.025,3,96 = 3.255 Fo.025,4,96 = 2.922 FO.95,3,96 = 0.117 Fo.95,4,96 = 0.177 Fo.975,3,96 = 0.072 Fo.975,4,96 = 0.120 What regression problem is evident from the Excel output?df SS MS F Regression 3 7.65E+10 2.55E+10 40.727 Residual 96 6.01E+10 6.26E+08 Total 99 1.37E+11 Coefficients Standard Error t Stat P-value Intercept 37717.595 14176.742 2.661 .01 Bedrooms 2306.081 6994.192 0.330 .74 House Size 74.297 52.979 1.402 .16 Lot Size -4.364 17.024 -0.256 .79 Fo.05,3,96 = 2.699 Fo.05,4,96 = 2.466 Fo.025,3,96 = 3.255 Fo.025,4,96 = 2.922 Fo.95,3,96 = 0.117 Fo.95,4,96 = 0.177 Fo.975,3,96 = 0.072 F0.975,4,96 = 0.120 What regression problem is evident from the Excel output? Select one: O a. Since the overall F is significant and the individual tests on slope are not significant, this indicates a problem with serious multicollinearity O b. Since the overall F is significant and the individual tests on slope are not significant, this indicates a problem with autocorrelation O c. All regression assumptions have been satisfied. O d. Since the overall F is significant and the individual tests on slope are not significant, this indicates a problem with nonconstant variance of the error term O'e. Since R2 is below .8, this regression is not valid