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A regression model to predict Y , the state-by-state burglary crime rate per 100,000 people, used the following four state predictors: X 1 = median

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

4,090.3389

AgeMed

-28.673

Bankrupt

20.2148

FedSpend

-0.0347

HSGrad%

-29.3008

(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 state-by-state crime rate per 100,000 multiple choice 1

  • decreases by about 29 as the state median age increases.
  • increases by about 29 as the state median age increases.

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

  • decreases by about 20 for every 1,000 new bankruptcies filed.
  • increases by about 20 for every 1,000 new bankruptcies filed.

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

  • decreases by 0.0347 for each dollar increase in federal funding per person.
  • increases by 0.0347 for each dollar increase in federal funding per person.

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

  • increases by about 29 for each 1% increase in high school graduations.
  • decreases by about 29 for each 1% increase in high school graduations.

(c) Would the intercept seem to have meaning in this regression? multiple choice 5

  • Yes
  • No

(d) Make a prediction for Burglary when X1 = 36 years, X2 = 6.7 bankruptcies per 1,000, X3 = $7,821, and X4 = 64 percent. (Round your answers to 4 decimal places.)

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