HW ILR - Chapter 8 (SDM) Linear Regression 2) Regression...

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Chapter 8 (SDM) Linear Regression 2) Regression Equations x s x y s y r ŷ = b o + b 1 x 30 4 18 6 -0.2 ŷ = 27 –0.3x 100 18 60 10 0.9 ŷ = 10 + 0.5x 4 0.8 50 15 0.8 ŷ = -10 + 15x 6 1.2 18 4 -0.6 ŷ = 30- 2x a) b 1 = rs y /s x = (-0.2)(6)/(4) = b 1 =-0.3 ŷ = b o + b 1 x y = b o + b 1 x 18 = b o + (-0.3)(30) 18 = b o + (-9) b 0 = 27 So, ŷ = 27- 0.3x b) b 1 = rs y /s x = (0.9)(10)/(18) = b 1 =0.5 ŷ = b o + b 1 x y = b o + b 1 x 60 = b o + (0.5)(100) 60 = b o + (50) b 0 = 10 So, ŷ = 10 + 0.5x c) ŷ = b o + b 1 x y = b o + b 1 x 50 = (-10) + (15)x 60 = 15x x = 4 b 1 = rs y /s x r =(s x )(b 1 )/(S y ) (0.8)(15)/(15) r = 0.8 d) ŷ = b o + b 1 x y = b o + b 1 x 18 = (30) - (2)x -12 = -2x x = 6 b 1 = rs y /s x s x = rs y /b 1 (-0.6)(4)/(-2) s x = 1.2
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4) Residuals a. The residual plot has a curved pattern. This indicates that the linear model is not appropriate. The relationship is not linear. b. The residual plot has a fanned pattern that indicates the linear model is not appropriate. The models predicting power increases as the values of the explanatory variable decrease. c. The scattered residual plot indicates that it is an appropriate linear model. 8) Roller Coaster
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This note was uploaded on 10/02/2008 for the course ILRST 2100 taught by Professor Vellemanp during the Fall '07 term at Cornell.

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HW ILR - Chapter 8 (SDM) Linear Regression 2) Regression...

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