You are part of a team investigating the identifying motor vehicle accidents. A multiple regression model is to be constructed to predict the number of motor vehicle accidents in a town per year based upon the population of the town, the number of recorded traffic offenses per year and the average annual temperature in the town. Data has been collected on 30 randomly selected towns: show data a) Find the multiple regression equation using all three explanatory variables. Assume that X, is population, X2 is number of recorded traffic offenses per year and X3 is average annual temperature. Give your answers to 3 decimal places. y = population + no. traffic offences + average temp b) At a level of significance of 0.05, the result of the F test for this model is that the null hypothesis rejected. For parts c) and d), using the data, separately calculate the correlations between the response variable and each of the three explanatory variables. c) The explanatory variable that is most correlated with number of motor vehicle accidents per year is: population number of traffic offenses average annual temperature d) The explanatory variable that is least correlated with number of motor vehicle accidents per year is: population number of traffic offenses average annual temperature e) The value of R2 for this model, to 2 decimal places, is equal to f) The value of se for this model, to 3 decimal places, is equal to g) Construct a new multiple regression model by removing the variable average annual temperature. Give your answers to 3 decimal places. The new regression model equation is: y = 1 +L population + no. traffic offences h) In the new model compared to the previous one, the value of RZ (to 2 decimal places) is: O increased O decreased O unchanged i) In the new model compared to the previous one, the value of se (to 3 decimal places) is: O increased O decreased unchanged