Introduction 1 1.2 Notation and terminology 2 1.3 Definition of probability \ 9 1.4 Some properties of probability 1.5 Conditional probability 1.6 Counting techniques Summary Exercises CHAPTER & RANDOM VARIABLES AND THEIR DISTRIBUTIONS 53 2.1 Introduction 2.2 Discrete random variables 2.3 Continuous random variables 2.4 Some properties of expected values 2.5 Moment generating functions Summary Exercises VI CONTENTS CHAPTER SPECIAL PROBABILITY DISTRIBUTIONS 90 3.1 Introduction 90 3.2 Special discrete distributions 91 3.3 Special continuous distributions 109 3.4 Location and scale parameters 124 Summary 127 Exercises 128 CHAPTER 4 JOINT DISTRIBUTIONS 136 4.1 Introduction 136 4.2 Joint discrete distributions 4.3 Joint continuous distributions 4.4 Independent random variables 4.5 Conditional distributions 4.6 Random samples Summary Exercises CHAPTER PROPERTIES OF RANDOM VARIABLES 171 5.1 Introduction 5.2 Properties of expected values 5.3 Correlation 5.4 Conditional expectation 5.5 Joint moment generating functions Summary Exercises CONTENTS vii CHAPTER 1/ FUNCTIONS OF RANDOM VARIABLES 193 6.1 Introduction 6.2 The CDF technique 6.3 Transformation methods 6.4 Sums of random variables 6.5 Order statistics Summary Exercises CHAPTER / LIMITING DISTRIBUTIONS 231 7.1 Introduction 7.2 Sequences of random variables 7.3 The central limit theorem 7.4 Approximations for the binomial distribution 7.5 Asymptotic normal distributions 7.6 Properties of stochastic convergence 7.7 Additional limit theorems 7.8* Asymptotic distributions of extreme-order statistics Summary Exercises CHAPTER 8 STATISTICS AND SAMPLING DISTRIBUTIONS 263 8.1 Introduction 8.2 Statistics 8.3 Sampling distributions 8.4 The t, F, and beta distributions 8.5 Large-sample approximations Summary Exercises * Advanced (or optional) topics vffi CONTENTS CHAPTER POINT ESTIMATION 288 9.1 Introduction 9.2 Some methods Of estimation 9.3 Criteria for evaluating estimators 9.4 Large-sample properties 9.

No abstract

No abstract

No abstract

No abstract