Cover 1
Title 4
Copyright 5
Contents 6
Preface 8
Prerequisites and Overview 10
Chapter 1. Modeling a Probabilistic Experiment 12
§1.1. Elementary Experiments 12
§1.2. Sequences of Elementary Experiments 14
Chapter 2. Random Variables 16
Chapter 3. Independence 20
Chapter 4. The Binomial Distribution 24
Chapter 5. The Weak Law of Large Numbers 28
Chapter 6. The Large Deviations Estimate 32
Chapter 7. The Central Limit Theorem 38
§7.1. Statement of the Theorem 38
§7.2. Remarks 39
§7.3. Applications 42
§7.4. Proof of the Theorem 45
Chapter 8. The Moderate Deviations Estimate 54
Chapter 9. The Local Limit Theorem 62
Chapter 10. The Arcsine Law 68
§10.1. Introduction 68
§10.2. Statement of the Theorems 69
§10.3. The Reflection Principle 70
§10.4. Proof of the Arcsine Law 75
§10.5. Proof of the Law of Returns to the Origin 82
Chapter 11. The Strong Law of Large Numbers 86
§11.1. Almost Sure Events, Independent Events 87
§11.2. Borel's Strong Law of Large Numbers 91
§11.3. Random Sequences Taking Several Values 94
§11.4. Normal Numbers 95
§11.5. The Borel-Cantelli Lemmas 98
Chapter 12. The Law of the Iterated Logarithm 106
§12.1. Introduction 106
§12.2. Hausdorff's Estimate 108
§12.3. Hardy and Littlewood's Estimate 109
§12.4. Khinchin's Law of the Iterated Logarithm 109
Chapter 13. Recurrence of Random Walks 118
§13.1. Introduction and Definitions 118
§13.2. Nearest Neighbor Random Walks on Z 120
§13.3. General Results about Random Walks 121
§13.4. Recurrence of Random Walks on ZN 136
Chapter 14. Epilogue 140
§14.1. A Few More General Results 140
§14.2. Closing Remarks 144
Biographies 146
Bibliography 156
Index 158
A 158
B 158
C 158
D 158
E 158
G 158
H 158
I 158
K 7
L 158
M 159
N 159
O 159
P 159
R 159
S 159
U 7
V 159
W 159
Back Cover 162
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