chapter 1

Chapter 13: Nonlinear and Multiple Regression48.a. H β = β = ... = β 00:1 29=H : at least one β ≠ 0aRR: f ≥ F .= 10. 16f01,9,52R=−n−k−1i.9389k2( )=( )= 8. 411−R1 .938( ) ( )5Fail to reject H o . The model does not appear to specify a useful relationship.b. µ ˆ = 21. 967 , t = t 2. 571yα / 2, n−(k+1) .025,5=( 2.571)( 1.248) ( 18.76,25.18)21 .967=± .2 SSE 23.379c. s = = = 4. 6758n − ( k + 1) 521.967d. = 23.379,, so the C.I. is, and the C.I. is( 2.571) 4.6758 + ( 1.248) 2 = ( 15.55,28.39)± .SSE SSE = 203.82,Hkl0: β4= β5= ... = β9=H : at least one of the above β ≠ 0a0i≥ Fα, k −l,n−(k + 1)= F.05,6,5=RR: f4. 95( 203.82−23.379) ( 9−3)f =( )= 6. 43 .23.379( )5Reject H o . At least one of the second order predictors appears useful.49.ˆy⋅18 .9, 43=a. µ 96.8303;Residual = 91 – 96.8303 = -5.8303.b. β = β 0H ; H : at least one β ≠ 00:1 2=RR: f ≥ F .= 8. 02f05,2,92R=−n−k−1k2( )=( )= 14. 901−R1 .768( )a.7682c. 96 .8303±( 2.262)( 8.20) = ( 78.28, 115.38)9i. Reject H o . The model appears useful.2 2d. 96.8303±( 2.262) 24.45 + 8.20 = ( 38.50, 155.16)421