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, 670.7702 AgeMed 26.356 Bankrupt 18. 1809 FedSpend -0. 0235 HSGrad* -25.9597 (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 statebystate crime rate per 100.000 0 decreases by about 26 as the state median age increases. 0 increases by about 26 as the state median age increases. (b-Z} The statebystate crime rate per 100.000 0 increases by about 18 for eyery1,000 new bankruptcies filed. 0 decreases by about 18 for every 1,000 newr bankruptcies filed. (la-3} The statebystate crime rate per 100,000 0 decreases by 0.0235 for each dollar increase in federal funding per person. 0 increases by 00235 for each dollar increase in federal funding per person. (b4) The statebystate crime rate per 100.000 0 decreases by about 26 for each 1% increase in high school graduations. 0 increases by about 26 for each 1% increase in high school graduations. (1:) Would the intercept seem to have meaning in this regression? 0 Yes O No (d) Make a prediction for Burglary when X1 = 35 years, X2 = 6.3 bankruptcies per 1,000, X; = $5,961, and X4 = 68 percent. (Round your answers to 4 decimal places.) Burglary Rate