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ercept Med krupt Spend rad% Coeffit Lent 4,198.5888 -27.3540 17.4893 -0.0124 -29.0314 ick here for the Excel Data File rite the fitted regression equation. (Round your answers to 4 decimal places. Negative values shoul ) Answer is complete but not ent

ercept Med krupt Spend rad% Coeffit Lent 4,198.5888 -27.3540 17.4893 -0.0124 -29.0314 ick here for the Excel Data File rite the fitted regression equation. (Round your answers to 4 decimal places. Negative values shoul ) Answer is complete but not ent

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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: X₁ =median age. X₂ = number of bankruptcies per 1,000 people, X3 = federal expenditures per capita, and X4 = high school graduation percentage. Predictor Intercept AgeMed Bankrupt Coefficient 4,198.5888 -27.3540 17.4893 -0.0124 FedSpend HSGrad% -29.0314 Click here for the Excel Data File (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be Indicated by a minus sign.) |ŷ = 4,670.7702 + -26.3560 AgeMed + (b-1) The state-by-state crime rate per 100,000 O decreases by about 17 as the state median age increases. O increases by about 27 as the state median age decreases. O increases by about 20 as the state median age decreases. O decreases by about 27 as the state median age increases. (b-2) The state-by-state crime rate per 100,000 X Answer is complete but not entirely correct. -0.0235 FedSpend + 18.1809 Bankrupt + (b-3) The state-by-state crime rate per 100,000 O decreases by about 7 for every 1,000 new bankruptcies filed. O increases by about 17 for every 1,000 new bankruptcies filed. O increases by about 27 for every 1,000 new bankruptcies filed. O decreases by about 17 for every 1,000 new bankruptcies filed. O decreases by .025 for each dollar increase in federal funding per person. O increases by .0124 for each dollar increase in federal funding per person. O decreases by .0124 for each dollar increase in federal funding per person. O increases bv .05 for each dollar increase in federal funding per person. -25.9597 HSGrad %6
Transcribed Image Text: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 Intercept AgeMed Bankrupt Coefficient 4,198.5888 -27.3540 17.4893 -0.0124 FedSpend HSGrad% -29.0314 Click here for the Excel Data File (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be Indicated by a minus sign.) |ŷ = 4,670.7702 + -26.3560 AgeMed + (b-1) The state-by-state crime rate per 100,000 O decreases by about 17 as the state median age increases. O increases by about 27 as the state median age decreases. O increases by about 20 as the state median age decreases. O decreases by about 27 as the state median age increases. (b-2) The state-by-state crime rate per 100,000 X Answer is complete but not entirely correct. -0.0235 FedSpend + 18.1809 Bankrupt + (b-3) The state-by-state crime rate per 100,000 O decreases by about 7 for every 1,000 new bankruptcies filed. O increases by about 17 for every 1,000 new bankruptcies filed. O increases by about 27 for every 1,000 new bankruptcies filed. O decreases by about 17 for every 1,000 new bankruptcies filed. O decreases by .025 for each dollar increase in federal funding per person. O increases by .0124 for each dollar increase in federal funding per person. O decreases by .0124 for each dollar increase in federal funding per person. O increases bv .05 for each dollar increase in federal funding per person. -25.9597 HSGrad %6
(b-4) The state-by-state crime rate per 100,000 Ⓒincreases by about 29 for each 1% increase in high school graduations. increases by about 19 for each 1% increase in high school graduations. decreases by about 19 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? Yes O No (d) Make a prediction for Burglary when X₂ = 35 years, X₂ = 7.0 bankruptcies per 1,000, X3 = $6,000, and X4 = 80 percent. Burglary Rate
Transcribed Image Text:(b-4) The state-by-state crime rate per 100,000 Ⓒincreases by about 29 for each 1% increase in high school graduations. increases by about 19 for each 1% increase in high school graduations. decreases by about 19 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? Yes O No (d) Make a prediction for Burglary when X₂ = 35 years, X₂ = 7.0 bankruptcies per 1,000, X3 = $6,000, and X4 = 80 percent. Burglary Rate
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