| preface 1 introduction 1.1 organization of text 1.2 probability tables and computer software 1.3 prerequisites part a: probability and random variables 2 basic probability concepts 2.1 elements of set theory 2.2 sample space and probability measure 2.3 statistical independence 2.4 conditional probability reference further reading problems 3 random variables and probability distributions 3.1 random variables 3.2 probability distributions 3.3 two or more random variables 3.4 conditional distribution and independence further reading and comments . problems 4 expectations and moments 4.1 moments of a single random variable 4.2 chebyshev inequality 4.3 moments of two or more random variables 4.4 moments of sums of random variables 4.5 characteristic functions further reading and comments problems 5 functions of random variables 5.1 functions of one random variable 5.2 functions of two or more radom variables 5.3 m functions of n random variables reference problems 6 some important discrete distributions 6.1 bernoulli trials …… 7 some important continuous distributions part b: statistical inference, parameter estimation, and model verification 8 observed data and graphical representation 9 parameter estimation 10 model verification 11 linear models and linear regression appendix a: tables appendix b: computer software appendix c: answers to selected problems subject index |
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