管理經(jīng)濟(jì)學(xué)（英文版 第8版）

Chapter 1　Introduction.　1  
1-1　Strategy of Experimentation　  
1-2　Some Typical Applications of Experimental Design　8  
1-3　Basi Principles　12  
1-4　Guidelines for Designing Experiments　1  
1-5　A Brief History of Statistical Design　19  
1-6　Summary: Using Statistical Techniques in Experimentation　21  
1- 　Problems　22  
Chapter 2　Simple Comparative Experiments　23  
2-1　Introduction　23  
2-2　Basi Statistical Concepts　24  
2-3　Sampling and Sampling Distributions　28  
2-4　Inferences about the Differences in Means, Randomized Designs　34  
2-4.1　Hypothesis Testing　34  
2-4.2　Choice of Sample Size　41  
2-4.3　Confidence Intervals　43  
2-4.4　The Case Where 　45  
2-4.5　The Case Where and Are Known　45  
2-4.6　Comparing a Single Mean to a Specified Value　46  
2-4.7　Summary　47  
2-5　Inferences about the Differences in Means, Paired Comparison Designs　48  
2-5.1　The Paired Comparison Problem　48  
2-5.2　Advantages of the Paired Comparison Design　51  
2-6　Inferences about the Variances of Normal Distributions　52  
2-7　Problems　54  
Chapter 3　Experiments with a Single Factor: The Analysis of Variance　60  
3-1　An Example　61  
3-2　The Analysis of Variance　63  
3-3　Analysis of the Fixed Effects Model　65  
3-3.1　Decomposition of the Total Sum of Squares　66  
3-3.2　Statistical Analysis　68  
3-3.3　Estimation of the Model Parameters　73  
3-3.4　Unbalanced Data　75  
3-4　Model Adequacy Che king　75  
3-4.1　The Normality Assumption　76  
3-4.2　Plot of Residuals in Time Sequence　78  
3-4.3　Plot of Residuals Versus Fitted Values　79  
3-4.4　Plots of Residuals Versus Other Variables　84  
3-5　Practical Interpretation of Results　85  
3-5.1　A Regression Model　85  
3-5.2　Comparisons Among Treatment Means　87  
3-5.3　Graphical Comparisons of Means　87  
3-5.4　Contrasts　88  
3-5.5　Orthogonal Contrasts　91  
3-5.6　Scheff??s Method for Comparing All Contrasts　93  
3-5.7　Comparing Pairs of Treatment Means　94  
3-5.8　Comparing Treatment Means withca Control　97  
3-6　Sample Computer Output　98  
3-7　Determining Sample Size　101  
3-7.1　Operating Characteristi Curves　101  
3-7.2　Specifying a Standard Deviation In rease　104  
3-7.3　Confidence Interval Estimation Method　104  
3-8　Dis overing Dispersion Effects　105  
3-9　The Regression Approach to the Analysis of Variance　107  
3-9.1　Least Squares Estimation of the Model Parameters　107  
3-9.2　The General Regression Significance Test　108  
3-10　Nonparametri Methods in the Analysis of Variance　110  
3-10.1　The KruskalDWallis Test　110  
3-10.2　General Comments on the Rank Transformation　112  
3-11　Problems　112  
Chapter 4　Randomized Blo ks, Latin Squares, and Related Designs　119  
4-1　The Randomized Complete Block Design　119  
4-1.1　Statistical Analysis of the RCBD　121  
4-1.2　Model Adequacy Checking　128  
4-1.3　Some Other Aspeccts of the Randomized Complete Block Design　130  
4-1.4　Estimating Model Parameters and the General Regression Significance Test　133  
4-2　The Latin Square Design　136  
4-3　The Graeco-Latin Square Design　142  
4-4　Balanced In omplete Block Designs　145  
4-4.1　Statistical Analysis of the BIBD　146  
4-4.2　Least Squares Estimation of the Parameters　150  
4-4.3　Recovery of Interblock Information in the BIBD　152  
4-5　Problems　154  
Chapter 5　Introduction to Factorial Designs　160  
5-1　Basi Definitions and Principles　160  
5-2　The Advantage of Factorials　163  
5-3　The Two-Factor Factorial Design　164  
5-3.1　An Example　164  
5-3.2　Statistical Analysis of the Fixed Effects Model　167  
5-3.3　Model Adequacy Checking　172  
5-3.4　Estimating the Model Parameters　175  
5-3.5　Choice of Sample Size　177  
5-3.6　The Assumption of No Interaction in a Two-Factor Model　178  
5-3.7　One Observation per Cell　179  
5-4　The General Factorial Design　182  
5-5　Fitting Response Curves and Surfaces　188  
5-6　Blocking in a Factorial Design　193  
5-7　Problems　197  
Chapter 6　The 2k Factorial Design　203  
6-1　Introduction　203  
6-2　The 22 Design　204  
6-3　The 23 Design　211  
6-4　The General 2k Design　224  
6-5　A Single Replicate of the 2k Design　226  
6-6　The Addition of Center Points to the 2k Design　247  
6-7　Why We Work with Coded Design Variables　251  
6-8　Problems　254  
Chapter 7　Blocking and Confounding in the 2k Factorial Design　265  
7-1　Introduction　265  
7-2　Blocking a Replicated 2k Factorial Design　266  
7-3　Confounding in the 2k Factorial Design　266  
7-4　Confounding the 2k Factorial Design in Two Blocks　267  
7-5　Another Illustration of Why Blocking Is Important　273  
7-6　Confounding the 2k Factorial Design in Four Blocks　275  
7-7　Confounding the 2k Factorial Design in 2p Blocks　276  
7-8　Partial Confounding　278  
7-9　Problems　280  
Chapter 8　Two-Level Fractional Factorial Designs　282  
8-1　Introduction　282  
8-2　The One-Half Fraction of the 2k Design　283  
8-2.1　Definitions and Basic Principles　283  
8-2.2　Design Resolution　285  
8-2.3　Construction and Analysis of the One-Half Fraction　286  
8-3　The One-Quarter Fraction of the 2k Design　296  
8-4　The General 2k2p Fractional Factorial Design　303  
8-4.1　Choosing a Design　303  
8-4.2　Analysis of 2k2p Fractional Factorials　306  
8-4.3　Blocking Fractional Factorials　307  
8-5　Resolution III Designs　312  
8-5.1　Constructing Resolution III Designs　312  
8-5.2　Fold Over of Resolution III Fractions to Separate Aliased Effects　314  
8-5.3　PlackettDBurman Designs　319  
8-6　Resolution IV and V Designs　322  
8-6.1　Resolution IV Designs　322  
8-6.2　Sequential Experimentation with Resolution IV Designs　325  
8-6.3　Resolution V Designs　331  
8-7　Supersaturated Designs　333  
8-8　Summary　335  
8-9　Problems..　335  
Chapter 9　Three-Level and Mixed-Level Factorial and Fractional Factorial Designs　347  
9-1　The 3k Factorial Design　347  
9-1.1　Notation and Motivation for the 3k Design　347  
9-1.2　The 32 Design　349  
9-1.3　The 33 Design　351  
9-1.4　The General 3k Design　355  
9-2　Confounding in the 3k Factorial Design　356  
9-2.1　The 3k Factorial Design in Three Blocks　356  
9-2.2　The 3k Factorial Design in Nine Blocks　360  
9-2.3　The 3k Fa torial Design in 3p Blocks　360  
9-3　Fractional Replication of the 3k Factorial Design　361  
9-3.1　The One-Third Fraction of the 3k Factorial Design　361  
9-3.2　Other 3k2p Fractional Factorial Designs　364  
9-4　Factorials with Mixed Levels　365  
9-4.1　Factors at Two and Three Levels　366  
9-4.2　Factors at Two and Four Levels　367  
9-5　Problems　369  
Chapter 10　Fitting Regression Models　373  
10-1　Introduction 　373  
10-2　Linear Regression Models　374  
10-3　Estimation of the Parameters in Linear Regression Models　375  
10-4　Hypothesis Testing in Multiple Regression　388  
10-4.1　Test for Signifi ance of Regression　388  
10-4.2　Tests on Individual Regression Coefficients and Groups of Coefficients　390  
10-5　Confidence Intervals in Multiple Regression　393  
10-5.1　Confidence Intervalscon the Individual Regression Coeffi ients　393  
10-5.2　Confidence Interval on the Mean Response　394  
10-6　Prediction of New Response Observations　394  
10-7　Regression Model Diagnostics　396  
10-7.1　Scaled Residuals and PRESS　396  
10-7.2　Influence Diagnostics　399  
10-8　Testing for Lack of Fit　400  
10-9　Problems　401  
Chapter 11　Response Surface Methods and Designs　405  
11-1　Introduction to Response Surface Methodology　405  
11-2　The Method of Steepest Ascent　407  
11-3　Analysis of a Second-Order Response Surface　413  
11-3.1　Location of the Stationary Point　413  
11-3.2　Chara terizing the Response Surface　415  
11-3.3　Ridge Systems　422  
11-3.4　Multiple Responses　423  
11-4　Experimental Designs for Fitting Response Surfaces　427  
11-4.1　Designs for Fitting the First-Order Model　428  
11-4.2　Designs for Fitting the Second-Order Model　428  
11-4.3　Blocking in Response Surface Designs　436  
11-4.4　Computer-Generated (Optimal) Designs　439  
11-5　Mixture Experiments　444  
11-6　Evolutionary Operation　452  
11-7　Problems　458  
Chapter 12　Robust Parameter Design and Process Robustness Studies　464  
12-1　Introduction　464  
12-2　Crossed Array Designs　466  
12-3　Analysis of the Crossed Array Design　468  
12-4　Combined Array Designs and the Response Model Approach　471  
12-5　Choice of Designs　477  
12-6　Problems　480  
Chapter 13　Experiments with Random Factors　484  
13-1　The Random Effects Model　485  
13-2　The Two-Factor Factorial with Random Factors　490  
13-3　The Two-Factor Mixed Model　495  
13-4　Sample Size Determination with Random Effects　500  
13-5　Rules for Expected Mean Squares　501  
13-6　Approximate FcTests　505  
13-7　Some Additional Topics on Estimation of Variance Components　511  
13-7.1　Approximate Confidence Intervals on Variance Components　511  
13-7.2　The Modified Large-Sample Method　514  
13-7.3　Maximum Likelihood Estimation of Variance Components　516  
13-8　Problems　521  
Chapter 14　Nested and Split-Plot Designs　525  
14-1　The Two-Stage Nested Design　525  
14-1.1　Statistical Analysis　526  
14-1.2　Diagnosti Checking　531  
14-1.3　Variance Components　532  
14-1.4　Staggered Nested Designs　533  
14-2　The Generalcm-Stage Nested Design　534  
14-3　Designs with Both Nested and Factorial Factors　536  
14-4　The Split-Plot Design　540  
14-5　Other Variations of the Split-Plot Design　545  
14-5.1　Split-Plot Designs with More Than Two Factors　545  
14-5.2　The Split-Split-Plot Design　550  
14-5.3　The Strip-Split-Plot Design　552  
14-6　Problems　554  
Chapter 15　Other Design and Analysis Topics　559  
15-1　Nonnormal Responses and Transformations　560  
15-1.1　Selecting a Transformation: The BoxDCox Method　560  
15-1.2　The Generalized Linear Model　563  
15-2　Unbalanced Data in a Factorial Design　570  
15-2.1　Proportional Data: An Easy Case　571  
15-2.2　Approximate Methods　572  
15-2.3　The Exa t Method　574  
15-3　The Analysis of Covariance　574  
15-3.1　Description of the Procedure　576  
15-3.2　Computer Solution　583  
15-3.3　Development by the General Regression Significance Test　584  
15-3.4　Factorial Experiments with Covariates　586  
15D4　Repeated Measures　590  
15-5　Problems　592  
Bibliography　595  
Appendix　603  
Table I.　Cumulative Standard Normal Distribution　604  
Table II.　Percentage Points of the t Distribution　606  
Table III.　Percentage Points of the x2 Distribution　607  
Table IV.　Percentage Points of the F Distribution　608  
Table V.　Operating Characteristi Curves for the Fixed Effects Model Analysis of Variance　613  
Table VI.　Operating Characteristi Curves for the Random Effects Model Analysis of Variance　617  
Table VII.　Percentage Points of the Studentized Range Statisti 　621  
Table VIII.　Critical Values for Dunnett's Test for Comparing Treatments with a Control　623  
Table IX.　Coefficients of Orthogonal Polynomials　625  
Table X.　Alias Relationships for 2k-p Fractional Factorial Designs withck≤15 and n≤64　626  
Index　...638