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

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: 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.

(a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be indicated by a minus sign.)

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

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

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

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

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

(d) Make a prediction for Burglary when X1= 31 years, X2= 5.5 bankruptcies per 1,000, X3= $6,254, and X4= 70 percent.

Burglary Rate

rev: 09_26_2016_QC_CS-62964, 09_20_2017_QC_CS-101173

Predictor Coefficient   Intercept 4,761.0570      AgeMed -30.867      Bankrupt 19.4063      FedSpend -0.0292      HSGrad% -25.8664   

Explanation / Answer

Ans:

a)

Y'=4761.0570-30.8670*Agemed+19.4063*Bankrupt-0.0292*Fedspend-25.8664*HSGrad%

b-1)

decreases by about 31 as the state median age increases.

b-2)

increases by about 19 for every 1,000 new bankruptcies filed.

b-3)

decreases by 0.0292 for each dollar increase in federal funding per person.

b-4)

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

c)Yes

d)

Y'=4761.0570-30.8670*31+19.4063*5.5-0.0292*6254-25.8664*70

Y'=1917.65

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