A regression model to predict Y the statebystate 2005 burgla

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 Intercept AgeMed Bankrupt FedSpeno HSG rad% Coefficient 4,198.5808 -27.3540 17.4893 -0.0124 -29.0314 Click h for (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 increases by about 20 as the state median age decreases decreases by about 17 as the state median age increases decreases by about 27 as the state median age increases increases by about 27 as the state median age decreases (b-2) The 2005 state by state crime rate per 100,000 decreases by about 7 for every 1000 new bankruptcies filed decreases by about 17 for every 1000 new bankruptcies filed increases by about 27 for every 1000 new bankruptcies filed increases by about 17 for every 1000 new bankruptcies filed

Solution

a)

From the table,

y^ = 4198.5808 + (-27.3540)AgeMEd + (17.4893)Bankrupt + (-0.0124)FedSpend + (-29.0314)HSGrad

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b-1.

As the coefficient of AgeMed is negative, then

OPTION C: DECREASES BY ABOUT 27 AS THE STATE MEDIAN AGE INCREASES.

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b-2.

As the coefficient of Bankruptcy is +17, then

OPTION D: INCREASES BY ABOUT 17 FOR EVERY 1000 NEW BANKRUPTCIES FILED.

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b-3.

As the coefficient is -0.0124, (negative),

OPTION B: DECREASES BY 0.0124 for each dollar increase in federal funding per person.

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