A regression model to predict Y, the state-by-state burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age, X2 = number of bankruptcies per 1,000 people, X3 = federal expenditures per capita, and X4 = high school graduation percentage. Predictor Coefficient Intercept 4, 281. 8359 AgeMed -26.151 Bankrupt 19.9325 FedSpend -0. 0391 HSGrad* -29 . 8965 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) V = + AgeMed + Bankrupt + FedSpend + HSGrad% (b-1) The state-by-state crime rate per 100,000 O increases by about 26 as the state median age increases. O decreases by about 26 as the state median age increases. (b-2) The state-by-state crime rate per 100,000 O increases by about 20 for every 1,000 new bankruptcies filed. O decreases by about 20 for every 1,000 new bankruptcies filed.(b-3) The state-by-state crime rate per 100,000 O decreases by 0.0391 for each dollar increase in federal funding per person. O increases by 0.0391 for each dollar increase in federal funding per person. (b-4) The state-by-state crime rate per 100,000 O increases by about 30 for each 1% increase in high school graduations. O decreases by about 30 for each 1% increase in high school graduations. (c) Would the intercept seem to have meaning in this regression? O Yes O No (d) Make a prediction for Burglary when Xy =31years, X, =70 bankruptcies per 1,000, X3 = $6,350, and X, = 77 percent. (Round your answers to 4 decimal places.) Burglary Rate | |