chapter 1

Chapter 13: Nonlinear and Multiple Regression80.a.(.90) ( 15 )( )= 2. 4.10( )f =. Because 2.4 < 5.86, β = ... = β 04H cannot be rejected.0:115=There does not appear to be a useful linear relationship.b. The high R 2 value resulted from saturating the model with predictors. In general, onewould be suspicious of a model yielding a high R 2 value when K is large relative to n.c.2( R ) ( 15 )2( )≥ 5. 861−R( )42R1− Riff ≥ 21. 97522 21.975iff R ≥ = . 956522.97581.a. The relevant hypotheses are H β = ... = β 0 vs. H a : at least one amongβ ,...,β 1 5is not 0. 2.. 05,5,111= 290:15=F andf=(.827) ( 5 )( )= 106. 1. Because.173( )106.1≥ 2.29 , H o is rejected in favor of the conclusion that there is a useful linearrelationship between Y and at least one of the predictors.b.. 05,111= 1. 66± . β1is the expected change in mortality rate associated with a one-unit increase in the particlereading when the other four predictors are held fixed; we cab be 90% confident that .014β < .068.t , so the C.I. is . 041 ( 1.66)( .016) = .041±.027 = (.014,.068)