Question 13 (1 point) A student worked as an intern at "We Always Win" Car Insurance Company. She noticed that an individual's car insurance premium depends very much on the age of the individual. the number of traffic infringement notices they have received in the last 5 years, and the population density {number of people per square kilometre measured in hundreds] in the city in which they live. Sbe constructed a multiple regression model in Microsoft Excel and obtained the following information: Regression Analysis Multiple R 0.992 R Square 0.984 Adj. R Square 0.979 Standard Error Observations AN OVA M S F Signff F Regression 1332.95 236.93 0.0000 Residual 4.32 - Total Intercept Driver-Age Traffic Infringement Population Density Use the above summary output to answer all the following. a. State the multiple regression equation. b. Interpret the meaning of the coefficient of multiple determination. c. What will be the predicted insurance premium for a 30-year-old driver who received 4 traffic infringement notices in the last 5 years and living in a city that has a population density of 15? (You must show your workings). d. Interpret from a practical point of view the 'Age' coefficient -0.92. e.Determine which independent variables to include in the regression model and which are more important in predicting the dependent variable. Explain your reasoning. f. She thinks the variable: 'Comprehensive car insurance' (i.e. Whether or not the driver has a comprehensive car insurance policy) should be included into the regression model. Explain in detail how this should be done. Answer Part a (1 mark) in the box below