You collect data on 26 metropolitan areas to analyze average monthly debt paymen

Question

You collect data on 26 metropolitan areas to analyze average monthly debt payments in terms of income and the unemployment rate. The data are shown in the accompanying table. Use Table 4 Income (in $1,000s) Unemployment Debt Metropolitan Area Washington, D.C Seattle Baltimore Boston Denver San FrancisCO San Diego Sacramento Los Angeles Chicago Philadelphia Minneapolis New York Atlanta $103.5 6.3% $1,285 1,135 1,133 1,133 1,104 1,098 1,076 1,045 1,024 1,017 1,011 1,011 989 986 970 957 948 920 889 82.2 89.5 75.9 93.4 75.5 10.6 12.9 68.2 78.3 78.3 10.3 68.3 66.6 Phoenix Portland Cincinnat Houston Columbus St. Louis Miami Detroit Cleveland Tampa Pittsburgh 10.2 69.5 65.1 68.6 68.3 60.2 69.8 64.8 59.4 63.0 886 867 832 812 791 763 15.7 SOURCE: eFannieMae.com; bls.com, and Experian.com he a-1. Estimate the model Debt = 0 + 1 Inc + 2Unemp + . (Round your answers to 4 decimal places.) Debt Inc + Unemp a-2. Is unemployment significant at the 5% level? es 0 c-1. Estimate Debt = 0 + |Inc + 2Unemp + 3Unemp2 + (Negative values should be indicated by a minus sign. Round your answers to 4 decimal places.) Debt = Inc + Unemp+ Unem c-2. Determine if Unemp and Unemp2 are jointly significant at the 5% level O With the t-tests, we conclude that Unemp and Unemp2 are jointly significant. O With the +-tests, we cannot conclude that Unemp and Unemp2 are jointly significant. O With the partial F-test, we conclude that Unemp and Unemp2 are jointly significant. With the partial F-test, we cannot conclude that Unemp and Unemp2 are jointly significant

Explanation / Answer

(a1)Debt=198.9955+10.51*inc+0.6186*unemp

(a2)yes

p-value is less than alpha=0.05

(c1)Debt=-264.6230+11.4821*inc+73.9527*unemp-3.2393*unemp2

(c2) third, with partial F............

We use the F-test to evaluate hypotheses that involved multiple parameters

following information has been generated using ms-excel

SUMMARY OUTPUT Regression Statistics Multiple R 0.867561816 R Square 0.752663505 Adjusted R Square 0.731155983 Standard Error 64.60976155 Observations 26 ANOVA df SS MS F Significance F Regression 2 292170.7719 146085.4 34.99536 1.05394E-07 Residual 23 96011.68963 4174.421 Total 25 388182.4615 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 198.9955611 156.3619079 1.27266 0.215854 -124.4636877 522.4548099 income 10.51215911 1.47652528 7.119525 2.98E-07 7.457733866 13.56658435 unemp 0.618572208 6.867902274 0.090067 0.929014 -13.58876602 14.82591043 SUMMARY OUTPUT Regression Statistics Multiple R 0.879258984 R Square 0.77309636 Adjusted R Square 0.742154955 Standard Error 63.27429948 Observations 26 ANOVA df SS MS F Significance F Regression 3 300102.4481 100034.1 24.98582 2.82564E-07 Residual 22 88080.01345 4003.637 Total 25 388182.4615 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept -264.6230355 363.2412507 -0.7285 0.473989 -1017.939279 488.6932081 income 11.48205201 1.601799738 7.168219 3.47E-07 8.160122693 14.80398133 unemp 73.95267632 52.5339168 1.407713 0.17319 -34.99599838 182.901351 unemp2 -3.239278119 2.301405229 -1.40752 0.173246 -8.01210042 1.533544181

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