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Unformatted text preview: Question #1 You worked as an intern at We Always Win Car Insurance Company last summer and noticed that individual car insurance premium depended very much on the age of the individual, the number of traffic tickets received by the individual and the population density of the city in which the individual lived. To see if your conjecture is correct, you collected the following EXCEL data set . In EXCEL, run a regression of insurance premium in dollars per month of an individual (RATE) on age of the individual in years (AGE), number of tickets received by the individuals (TICKETS) and the population density in hundreds of persons per square mile in which the individual lived (DENSITY). From the regression output, 0.604292353 of the total variability in insurance premium could be explained by AGE, TICKET and DENSITY. Also the coefficient of determination adjusted for the degrees of freedom is 0.496372086 , the standard error of the estimate is 46.6128731 , the estimated average change in insurance premium for every ten additional tickets received is 367.8352132 dollars per month, while the estimated average change in insurance premium for every five additional years of age is 7.018193488 dollars per month. Question #2 You decided to predict gasoline prices in different cities and towns in the United States for your modelling project. Your dependent variable is price of gasoline per gallon and your independent variables are per capita income (in dollars), number of firms manufacturing parts of automobiles in and around the city, number of new businesses started over the last year, population density of the city (in 100's of persons per sq. mile), percentage of local taxes on gasoline (in %), and the number of people using public transportation per 100 people. Note: the numbers below are randomly generated and will likely change when a new quiz is loaded. You collected a sample of 33 cities and obtained an SSR= 137.1484. Which of the following statements is (are) t rue if S e 2 is 3.5602 ? Adjusted R 2 =0.5041 Adjusted R 2 =0.5970 If number of new businesses started and population density are removed from the regression model, R 2 can never increase. If number of new businesses started and population density are removed from the regression model, adjusted R 2 can never increase. Adjusted R 2 =92.5660 If number of new businesses started and population density are removed from the regression model, R 2 will definitely increase. If number of new businesses started and population density are removed from the regression model, adjusted R 2 will definitely increase. Adjusted R 2 =0.6726 Question #3 You decided to predict gasoline prices in different cities and towns in the United States for your modelling project. Your dependent variable is price of gasoline per gallon and your independent variables are per capita income (in dollars), number of firms manufacturing parts of automobiles in and around the city, number of new businesses started over the last...
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 Spring '09
 PETRY
 Regression Analysis, insurance premium, independent variables

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