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Solutions Manual to Accompany Introduction to Linear Regression Analysis, 5th Edition by Anne G. Ryan, G. Geoffrey Vining, Elizabeth A. Peck, Douglas C. Montgomery, Ann G. Ryan

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Chapter 14

Regression Analysis of Time Series Data

14.3 a.
= 24.6 − 0.0892x. The residual plot versus time indicates there is autocorrelation.
b. d = .81 which rejects the null hypothesis and indicates that there is evidence of positive autocorrelation.
c. We get

equation

The new regression equation is ′ = 12.0854 − 0.1105x
The standard errors of the regression coefficients are se(0) = 0.5542 and se(1) = 0.0.01403.
d. d = .90 which indicates there is still evidence of positive autocorrelation.
14.5
The regression through the origin for the first difference approach yields an estimataed slope of 0.28943 with a standard error of 0.02508. The previous estimate for 1 was 0.29799 with a standard error of 0.0123. As a result, the estimates are very similar, but the standard error is smaller for the ...

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