chapter 1

Chapter 13: Nonlinear and Multiple Regression56.a. = 20 , k = 5, n − ( k + 1) = 14n , so β = ... = β 0ofa:(.769)f0:15=1,..., β5≠ f01,5,14H will be rejected in favorH at least one among β 0 , if ≥ F .= 4. 69=. With5( )= 9.32 ≥ 4. 69 , so H o is rejected. Wood specific gravity appears to be.23114linearly related to at lest one of the five carriers.b. For the full model, adjustedR2=( 19)( .769)( 19)( .769)− 5= .68714− 4= .7072model, the adjusted R =.15, while for the reducedc. From a, SSE = (. 231)( .0196610) = . 004542SSEl=k(. 346)( .0196610) = . 006803, sof, andF 3.34 and 2.32 is not ≥ 3. 34 , we conclude that = β = β 0. 05,3,14==(.002261)3( )= 2. 32 . Since.004542141 2 4=x3−52.540x5−89.195d. x ′3== −.4665 and x ′5== . 21965.44473.6660y ˆ = .5255 − .0236 −.4665+ .0097 .2196 = . .e. 2. 110. 025,17=( )( ) ( )( ) 5386β .t (error df = n – (k+1) = 20 – (2+1) = 17 for the two carrier model), sothe desired C.I. is . 0236 ± 2.110 (.0046) = ( −.0333,−.0139)− .⎛ x − 52.540⎞⎛ −89.195⎞f. = .5255−.0236⎜3x⎟ + .0097⎜5⎟⎝ 5.4447 ⎠ ⎝ 3.6660 ⎠− .0236unstandardized model = −.0043345.447.0046unstandardized ˆβ3is = = −.000845 .5.447y , so ˆβ3for the, so= . The estimated sd of the2g. y ˆ = . 532 and s s = . 02058+βˆ+ βˆx′+ βˆx′03 35 5, so the P.I. is( 2.110)( .02058) = .532 ± .043 (.489,.575). 532=± .425