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Professionals in all areas - business; government; the
physical, life, and social sciences; engineering; medicine, etc.
This book uses examples, drawn from a variety of established texts,
and embeds them in a business or scientific context, seasoned with
a dash of humor, to emphasize the issues and ideas that led to the
experiment and the what-do-we-do-next? steps after the
experiment. Graphical data displays are emphasized as means of
discovery and communication and formulas are minimized, with a
focus on interpreting the results that software produce. The role
of subject-matter knowledge, and passion, is also illustrated. The
examples do not require specialized knowledge, and the lessons they
contain are transferrable to other contexts.
Fundamentals of Statistical Experimental Design and Analysis
introduces the basic elements of an experimental design, and the
basic concepts underlying statistical analyses. Subsequent chapters
address the following families of experimental designs:
Completely Randomized designs, with single or multiple
treatment factors, quantitative or qualitative
Randomized Block designs
Latin Square designs
Split-Unit designs
Repeated Measures designs
Robust designs
Optimal designs
Written in an accessible, student-friendly style, this book is
suitable for a general audience and particularly for those
professionals seeking to improve and apply their understanding of
experimental design.
Autorentext
Robert G. Easterling. Dr. Easterling is retired from Sandia National Laboratories where he was a statistical consultant, manager, and senior scientist. He is a Fellow of the American Statistical Association, a former Editor of Technometrics, and a recipient of the American Society for Quality's Brumbaugh Award. He holds a Ph.D. in statistics from Oklahoma State University.
Klappentext
Professionals in all areas business; government; the physical, life, and social sciences; engineering; medicine, etc. benefit from using statistical experimental design to better understand their worlds and then use that understanding to improve the products, processes, and programs they are responsible for. This book aims to provide the practitioners of tomorrow with a memorable, easy to read, engaging guide to statistics and experimental design.
This book uses examples, drawn from a variety of established texts, and embeds them in a business or scientific context, seasoned with a dash of humor, to emphasize the issues and ideas that led to the experiment and the what-do-we-do-next? steps after the experiment. Graphical data displays are emphasized as means of discovery and communication and formulas are minimized, with a focus on interpreting the results that software produce. The role of subject-matter knowledge, and passion, is also illustrated. The examples do not require specialized knowledge, and the lessons they contain are transferrable to other contexts.
Fundamentals of Statistical Experimental Design and Analysis introduces the basic elements of an experimental design, and the basic concepts underlying statistical analyses. Subsequent chapters address the following families of experimental designs:
Inhalt
Preface xiii
Acknowledgments xix
Credits xxi
1 Introduction 1
Motivation: Why Experiment? 1
Steps in an Experimental Program 2
Planning and analysis 2
Communication 3
Subject?]Matter Passion 4
Case Study 5
Overview of Text 9
Assignment 10
References 10
2 Fundamentals of Experimental Design 11
Introduction 11
Experimental Structure 13
Experimental units 13
Blocks and block structures 15
Treatments and treatment structures 17
Response measurement 19
Principles of Experimental Design 20
Replication 21
Randomization 22
Blocking 24
Control 26
Assignment 27
References 27
3 Fundamentals of Statistical Data Analysis 29
Introduction 29
Boys' Shoes Experiment 30
Experimental design 30
Graphical displays 31
Significance testing 34
Probability and probability distributions 34
Sign test 36
Misinterpretation of P?]values 38
Randomization test 39
Normal distribution theory t?]test 40
Summary and discussion: Significance tests 46
Economic analysis: The bigger picture 48
Statistical confidence intervals 50
Discussion 53
Why calculate statistical confidence limits? 54
Sample size determination 54
Tomato Fertilizer Experiment 56
Experimental design 56
Analysis 1: Plot the data 56
The value of randomization 58
The importance of ancillary data 59
A New Tomato Experiment 59
Analysis 1: Plot the data 59
Significance tests 62
Rank sum test 63
Randomization test 64
Normal theory t?]test 66
Confidence intervals 69
Determining the size of an experiment 71
Comparing Standard Deviations 77
Discussion 79
Appendix 3.A The Binomial Distribution 79
Appendix 3.B Sampling from a Normal Distribution 81
Appendix 3.C Statistical Underpinnings 85
Single sample 86
Two samples 87
Assignment 89
References 89
4 Completely Randomized Design 91
Introduction 91
Design Issues 92
CRD: Single Qualitative Factor 92
Example: Market research 92
Analysis of Variance 95
Within?]group variation 96
Among?]groups variation 97
The F?]test 98
Analysis of variance 99
Discussion 100
Results 101
Testing the Assumptions of Equal Variances and Normality 103
Confidence Intervals 103
Inference 105
Statistical Prediction Interval 105
Example: Tomato Fertilizer Experiment Revisited 106
Sizing a Completely Randomized Experiment 107
CRD: Single Quantitative Factor 107
Example: Growth rate of rats 108
Graphical display 109
Curve fit 109
Analysis of variance 111
Design Issues 113
Enhanced Case Study: Power Window Gear Teeth 114
Graphical display 117
ANOVA 119
Discussion 120
Assignment 120
References 121
5 Completely Randomized Design with Multiple Treatment Factors 123
Introduction 123
Design Issues 124
Example 1 (Two qualitative factors): Poisons and antidotes 124
Analysis 1: Plot the data 126
Eyeball analysis 126
Interaction 128
ANOVA 130
Generalizing the ANOVA for a CRD with two factors 131
Antidote B versus Antidote D 132
Estimation of effects 133 Prediction intervals 135<...