Page 12 - Applied Statistics And Probability For Engineers

PQ220 6234F.FM 5/30/02 1:02 PM Page xii RK UL 6 RK UL 6:Desktop Folder:untitled folder:

xii CONTENTS

10-6 Inference on Two Population 12-1.1 Introduction 411
Proportions 361 12-1.2 Least Squares Estimation of the
10-6.1 Large-Sample Test for Parameters 414
361 12-1.3 Matrix Approach to Multiple
H 0 : p 1 p 2
10-6.2 Small Sample Test for Linear Regression 417
H 0 : p 1 p 2 (CD Only) 364 12-1.4 Properties of the Least Squares
Estimators 421
10-6.3 -Error and Choice of
Sample Size 364 12-2 Hypothesis Tests in Multiple Linear
10-6.4 Confidence Interval for Regression 428
365 12-2.1 Test for Significance of
P 1 P 2
10-7 Summary Table for Inference Regression 428
Procedures for Two Samples 367 12-2.2 Tests on Individual Regression
Coefficients and Subsets of
Coefficients 432
CHAPTER 11 Simple Linear 12-2.3 More About the Extra Sum of
Regression and Correlation 372 Squares Method (CD Only) 435
12-3 Confidence Intervals in Multiple
11-1 Empirical Models 373 Linear Regression 437
11-2 Simple Linear Regression 375
12-3.1 Confidence Intervals on Individual
11-3 Properties of the Least Squares
Regression Coefficients 437
Estimators 383
12-3.2 Confidence Interval on the Mean
11-4 Some Comments on Uses of Response 438
Regression (CD Only) 384 12-4 Prediction of New Observations 439
11-5 Hypothesis Tests in Simple Linear 12-5 Model Adequacy Checking 441
Regression 384 12-5.1 Residual Analysis 441
11-5.1 Use of t-Tests 384 12-5.2 Influential Observations 444
11-5.2 Analysis of Variance Approach 12-6 Aspects of Multiple Regression
to Test Significance of Modeling 447
Regression 387
12-6.1 Polynomial Regression
11-6 Confidence Intervals 389 Models 447
11-6.1 Confidence Intervals on the 12-6.2 Categorical Regressors and
Slope and Intercept 389 Indicator Variables 450
11-6.2 Confidence Interval on the 12-6.3 Selection of Variables and Model
Mean Response 390 Building 452
11-7 Prediction of New Observations 392 12-6.4 Multicollinearity 460
11-8 Adequacy of the Regression 12-6.5 Ridge Regression
Model 395 (CD Only) 461
11-8.1 Residual Analysis 395 12-6.6 Nonlinear Regression Models
11-8.2 Coefficient of Determination (CD Only) 461
2
(R ) 397
11-8.3 Lack-of-Fit Test CHAPTER 13 Design and
(CD Only) 398 Analysis of Single-Factor
11-9 Transformations to a Straight Experiments: The Analysis
Line 400 of Variance 468
11-10 More About Transformations
(CD Only) 400 13-1 Designing Engineering
11-11 Correlation 400 Experiments 469
13-2 The Completely Randomized
CHAPTER 12 Multiple Linear Single-Factor Experiment 470
Regression 410 13-2.1 An Example 470
13-2.2 The Analysis of Variance 472
12-1 Multiple Linear Regression 13-2.3 Multiple Comparisons Following
Model 411 the ANOVA 479