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

Question

A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors. X_1 = median age in 2005, X_2 = number of 2005 bankruptcies per 1,000 people, X_3 = 2004 federal expenditures per capita, and X_4 = 2005 high school graduation percentage. (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.) = + AgeMed + Bankrupt + FedSpend + HSGrad% (b-1) The 2005 state-by-state crime rate per 100,000 decreases by about 26 as the state median age increases. increases by about 26 as the state median age increases. (b-2) The 2005 state-by-state crime rate per 100,000 decreases by about 16 for every 1,000 new bankruptcies filed. increases by about 16 for every 1,000 new bankruptcies filed. (b-3) The 2005 state-by-state crime rate per 100,000 decreases by 0.0316 for each dollar increase in federal funding per person. increases by 0.0316 for each dollar increase in federal funding per person. (b-4) The 2005 state-by-state crime rate per 100,000 decreases by about 28 for each 1% increase in high school graduations. increases by about 28 for each 1% increase in high school graduations. (c) Would the intercept seem to have meaning in this regression? Yes No (d) Make a prediction for Burglary when X_1 =36 years, X_2 = 6.0 bankruptcies per 1,000, X_3 = $7,355, and X_4 = 74 percent. Sales $

Explanation / Answer

a) yhat=4318.7298+(-25.772)*Agemed+15.8250*bankrupt+(-0.0316)*fedspend+(-27.7307)*HSgard

b-1) decreases by about 26........

b-2)increase by

b-3)decreases by

b-4) decreases by

c)No ; as all other parameter can not all be 0.

d)

prediction ==4318.7298+(-25.772)*36+15.8250*6+(-0.0316)*7355+(-27.7307)*74=1201.3980

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