Regression analysis
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6. The National Transportation Safety Board collects Data by state (Including the District of Columbia) on traffic fatalities. Part of this data is shown in the following table, along with potentially related factors including populations numbers of licensed drivers, number of resisted vehicles and total number of vehicle miles drive. (The complete data are available in the file Trafrfic.xls.) You have been asked to develop a model to help explain the factor that underlie traffic fatalities.
Vehicle
Licensed Registered miles
Traffic Population Drivers Vehicles traveled
State Fatalities (Thous) (Thous) (Thous) (Millions)
AL 1083 4219 3043 3422 48956
AK 85 606 443 508 4150
AZ 903 4075 2654 2980 38774
AR 610 2453 1770 1560 24948
ca 4226 31431 20359 23518 271943
cO 585 3656 2620 3144 33705
CT 310 3275 2205 2638 27138
DE 112 706 512 568 7025
DC 69 570 366 270 3448
FL 2687 13953 10885 10132 121989
a. Build a linear model to predict traffic fatalities based on all four potential explanatory variables as they are measured in the table. Evaluate the results for each regression parameter: Are the signs appropriate? Are the values different from zero?
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Solution Summary
Step-by-step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.
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