A regression model to predict Y,the state-by-state 2005 burglary crime rate per 100.000 people, used the...

 

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A regression model to predict Y,the state-by-state 2005 burglary crime rate per 100.000 people, used the following four state predictors: X1, = median age in 2005, X2= number of 2005 bankruptcies per 1.000 people. X3 = 2004federalexpenditures per capita, and X4= 2005 high School graduation percentage. (a)Write the fit ted regression equation. (b) Interpret each coefficient. (c) Would the intercept seem to haw meaning in this regression? (d) Make a prediction for Burglarywhen XI= 35 years. X2= 7.0 bankruptcies per 1,000, X3= $6.000, and X4 = 80 percent Predictor Coefficient Intercept 4,198.5808 Age Med -27.35 40 Bankrupt 17.4893 Fed Spend -0.0124 HS Grad% -29.0314 A regression model to predict Y,the state-by-state 2005 burglary crime rate per 100.000 people, used the following four state predictors: X1, = median age in 2005, X2= number of 2005 bankruptcies per 1.000 people. X3 = 2004federalexpenditures per capita, and X4= 2005 high School graduation percentage. (a)Write the fit ted regression equation. (b) Interpret each coefficient. (c) Would the intercept seem to haw meaning in this regression? (d) Make a prediction for Burglarywhen XI= 35 years. X2= 7.0 bankruptcies per 1,000, X3= $6.000, and X4 = 80 percent Predictor Coefficient Intercept 4,198.5808 Age Med -27.35 40 Bankrupt 17.4893 Fed Spend -0.0124 HS Grad% -29.0314

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