Applied Linear Statistical Models 5th Ed. Solutions Manual (Kutner)

A COMPLETE Solutions
Manual FOR Applied
Linear
Statistical Models
Fifth Edition

,Contents

1 LINEAR REGRESSION WITH ONE PREDICTOR VARIABLE 1-1

2 INFERENCES IN REGRESSION AND CORRELATION ANALYSIS 2-1

3 DIAGNOSTICS AND REMEDIAL MEASURES 3-1

4 SIMULTANEOUS INFERENCES AND OTHER TOPICS IN REGRES-
SION ANALYSIS 4-1

5 MATRIX APPROACH TO SIMPLE LINEAR REGRESSION ANALY-
SIS 5-1

6 MULTIPLE REGRESSION – I 6-1

7 MULTIPLE REGRESSION – II 7-1

8 MODELS FOR QUANTITATIVE AND QUALITATIVE PREDICTORS 8-1

9 BUILDING THE REGRESSION MODEL I: MODEL SELECTION AND
VALIDATION 9-1

10 BUILDING THE REGRESSION MODEL II: DIAGNOSTICS 10-1

11 BUILDING THE REGRESSION MODEL III: REMEDIAL MEASURES11-1

12 AUTOCORRELATION IN TIME SERIES DATA 12-1

13 INTRODUCTION TO NONLINEAR REGRESSION AND NEURAL NET-
WORKS 13-1

14 LOGISTIC REGRESSION, POISSON REGRESSION,AND GENERAL-
IZED LINEAR MODELS 14-1

15 INTRODUCTION TO THE DESIGN OF EXPERIMENTAL AND OB-
SERVATIONAL STUDIES 15-1

16 SINGLE-FACTOR STUDIES 16-1

17 ANALYSIS OF FACTOR LEVEL MEANS 17-1

ii

,18 ANOVA DIAGNOSTICS AND REMEDIAL MEASURES 18-1

19 TWO-FACTOR STUDIES WITH EQUAL SAMPLE SIZES 19-1

20 TWO-FACTOR STUDIES – ONE CASE PER TREATMENT 20-1

21 RANDOMIZED COMPLETE BLOCK DESIGNS 21-1

22 ANALYSIS OF COVARIANCE 22-1

23 TWO-FACTOR STUDIES – UNEQUAL SAMPLE SIZES 23-1

24 MULTIFACTOR STUDIES 24-1

25 RANDOM AND MIXED EFFECTS MODELS 25-1

26 NESTED DESIGNS, SUBSAMPLING, AND PARTIALLY NESTED DE-
SIGNS 26-1

27 REPEATED MEASURES AND RELATED DESIGNS 27-1

28 BALANCED INCOMPLETE BLOCK, LATIN SQUARE, AND RELATED
DESIGNS 28-1

29 EXPLORATORY EXPERIMENTS – TWO-LEVEL FACTORIAL AND
FRACTIONAL FACTORIAL DESIGNS 29-1

30 RESPONSE SURFACE METHODOLOGY 30-1




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, Chapter 1

LINEAR REGRESSION WITH ONE
PREDICTOR VARIABLE

1.20. a. Ŷ = −0.5802 + 15.0352X
d. Yˆ h = 74.5958
1.21. a. Ŷ = 10.20 + 4.00X
b. Yˆ h = 14.2
c. 4.0
d. ( X̄ , Ȳ ) = (1, 14.2)
i: 1 2 ... 44 45
1.24. a.
ei: -9.4903 0.4392 . . . 1.4392 2.4039
Σ
ei2 = 3416.377
Min Q = Σ ei2
√
b. MSE = 79.45063, MSE = 8.913508, minutes

1.25. a. e1 = 1.8000
Σ
b. e2i = 17.6000, MSE = 2.2000, σ2

1.27. a. Ŷ = 156.35 − 1.19X
b. (1) b1 = −1.19, (2) Yˆ h = 84.95, (3) e8 = 4.4433,
(4) MSE = 66.8




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