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作者:Dennis D. Wackerly
University of Florida
William Mendenhall III
University of Florida, Emeritus
Richard L. Scheaffer
University of Florida, Emeritus
页数939
出版社Thomson Higher Education
ISBN-13: 978-0-495-38508-0
ISBN-10: 0-495-38508-5
目录Preface xiii
Note to the Student xxi
1 What Is Statistics? 1
1.1 Introduction 1
1.2 Characterizing a Set of Measurements: Graphical Methods 3
1.3 Characterizing a Set of Measurements: Numerical Methods 8
1.4 How Inferences Are Made 13
1.5 Theory and Reality 14
1.6 Summary 15
2 Probability 20
2.1 Introduction 20
2.2 Probability and Inference 21
2.3 A Review of Set Notation 23
2.4 A Probabilistic Model for an Experiment: The Discrete Case 26
2.5 Calculating the Probability of an Event: The Sample-Point Method 35
2.6 Tools for Counting Sample Points 40
2.7 Conditional Probability and the Independence of Events 51
2.8 Two Laws of Probability 57
v2.9 Calculating the Probability of an Event: The Event-Composition
Method 62
2.10 The Law of Total Probability and Bayes’ Rule 70
2.11 Numerical Events and Random Variables 75
2.12 Random Sampling 77
2.13 Summary 79
3 Discrete Random Variables and Their
Probability Distributions 86
3.1 Basic Definition 86
3.2 The Probability Distribution for a Discrete Random Variable 87
3.3 The Expected Value of a Random Variable or a Function
of a Random Variable 91
3.4 The Binomial Probability Distribution 100
3.5 The Geometric Probability Distribution 114
3.6 The Negative Binomial Probability Distribution (Optional) 121
3.7 The Hypergeometric Probability Distribution 125
3.8 The Poisson Probability Distribution 131
3.9 Moments and Moment-Generating Functions 138
3.10 Probability-Generating Functions (Optional) 143
3.11 Tchebysheff’s Theorem 146
3.12 Summary 149
4 Continuous Variables and Their Probability
Distributions 157
4.1 Introduction 157
4.2 The Probability Distribution for a Continuous Random Variable 158
4.3 Expected Values for Continuous Random Variables 170
4.4 The Uniform Probability Distribution 174
4.5 The Normal Probability Distribution 178
4.6 The Gamma Probability Distribution 185
4.7 The Beta Probability Distribution 194
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