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D make a prediction for sales when floorspace 107

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d. Make a prediction for Sales when FloorSpace = 107, CompetingAds = 94 and Price =1173.PredictorCoecientIntercept1210.39FloorSpace10.35CompetingAds-6.803Price-0.1414
54. A regression model to predictY, the state-by-state 2005 burglary crime rate per100,000 people, used the following four state predictors:X1= median age in 2005,X2number of 2005 bankruptcies per 1,000 people,X3= 2004 federal expenditures percapita, andX4= 2005 high school graduation percentage.PredictorCoeceintIntercept4459.7813AgeMed-26.190Bankrupt16,9037=
a. Write the fitted regression equation.FedSpend-0.0161MSGrad%-30.9882
b2. The 2005 state-by-state crime rate per 100,000increases by about 17 for every 1,000 new bankruptcies filed.
c. Could the intercept seem to have meaning in this regression?
d. Make a prediction forBurglarywhenX1= 34 years,X2= 7.9bankruptciesper 1,000,X3= $7,959, andX4= 89 percent.
55. Refer to ANOVA table for this regression.a. State the degrees of freedom for the F test for overall significance.SourcedfSSMSRegression28742643713Error2437612015672Total26463546
b. Use Appendix F to look up the critical value of F for a = .05.
c1. Calculate the F statistic.
c2. The overall regression is significant.
c3. The hypotheses are: a)H0: All the coefficients are zero (β1=β2=β3= 0) vs.H1: Atleast one coefficient is not zero. b)H0: At least one coefficient is non-zero vs.H1: All thecoefficients are zero (β1=β2=β3= 0)ad. Calculate R^2 and R^2adj.
56. Refer to the ANOVA table for this regression.a. State the degrees of freedom for the F test for overall significance.SourceSSdfMSRegression11645785232916Residual15006894533349Total266526750
b. Use Appendix F to look up the critical value of F for a = .05.
c1. Calculate the F statistic.: At
d. Calculate R^2 and R^2 adj.
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Fall
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Regression Analysis, Variance, regression model s F test statistic

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