Consider the following computer output from a multiple regression analysis relating the cost of car insurance to the variables: number of car accidents, driver’s credit score, and safety rating of the car.   Coefficients Standard Error t Coefficients Stat P-value Intercept 1117   113.71   9.823   0.0000   Car Accidents (In last 3 years) 201.06   20.67   9.727   0.0000   Credit Score −122.87   13.47   −9.122   0.0000   Safety Rating −268.22   26.94   −9.956   0.0000   Does the sign of the coefficient for the variable safety rating make sense?

The systolic blood pressure of individuals is thought to be related to both age and weight. Let the systolic blood pressure, age, and weight be represented by the variables x1, x2, and x3, respectively. Suppose that Minitab was used to generate the following descriptive statistics, correlations, and regression analysis for a random sample of 15 individuals.  Descriptive Statistics Variable N Mean Median TrMean StDev SE Mean x1 15 158.42 158.72 158.42 3.127 0.807388 x2 15 65.95 66.45 65.95 1.091 0.281695 x3 15 187.23 186.63 187.23 4.171 1.076948   Variable Minimum Maximum Q1 Q3 x1 124 174 135.828 166.400 x2 41 80 47.088 77.579 x3 124 244 142.885 223.525   Correlations (Pearson)   x1 x2 x2 0.829   x3 0.860 0.661 Regression Analysis  The regression equation is  x1 = 0.837 + 1.120x2 + 0.928x3    Predictor Coef StDev T P…

In a multiple regression analysis involving an intercept, 15 independent variables  and 200 observations, Total SS = 800 and Residual SS = 240. Adjusted R-squared is

Please help me with question d, e, f, g, h, and I. Thank you.