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 = 2004 federal expenditures per capita, and X4 = 2005 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.)

3formula14.mml =

+

AgeMed +

Bankrupt +

FedSpend +

HSGrad%

(b-1) The 2005 state-by-state crime rate per 100,000

increases by about 26 as the state median age increases.

decreases by about 26 as the state median age increases.

(b-2) The 2005 state-by-state crime rate per 100,000

decreases by about 18 for every 1,000 new bankruptcies filed.

increases by about 18 for every 1,000 new bankruptcies filed.

(b-3) The 2005 state-by-state crime rate per 100,000

increases by 0.0235 for each dollar increase in federal funding per person.

decreases by 0.0235 for each dollar increase in federal funding per person.

(b-4) The 2005 state-by-state crime rate per 100,000

increases by about 26 for each 1% increase in high school graduations.

decreases by about 26 for each 1% increase in high school graduations.

(c) Would the intercept seem to have meaning in this regression?

No

Yes

(d) Make a prediction for Burglary when X1 = 35 years, X2 = 6.3 bankruptcies per 1,000, X3 = $5,961, and X4 = 68 percent.

Burglary Rate