Author | Pitman, Jim. author |
---|---|

Title | Probability [electronic resource] / by Jim Pitman |

Imprint | New York, NY : Springer New York, 1993 |

Connect to | http://dx.doi.org/10.1007/978-1-4612-4374-8 |

Descript | XI, 560 p. online resource |

SUMMARY

Preface to the Instructor This is a text for a one-quarter or one-semester course in probability, aimed at stuยญ dents who have done a year of calculus. The book is organized so a student can learn the fundamental ideas of probability from the first three chapters without reliance on calculus. Later chapters develop these ideas further using calculus tools. The book contains more than the usual number of examples worked out in detail. It is not possible to go through all these examples in class. Rather, I suggest that you deal quickly with the main points of theory, then spend class time on problems from the exercises, or your own favorite problems. The most valuable thing for students to learn from a course like this is how to pick up a probability problem in a new setting and relate it to the standard body of theory. The more they see this happen in class, and the more they do it themselves in exercises, the better. The style of the text is deliberately informal. My experience is that students learn more from intuitive explanations, diagrams, and examples than they do from theoยญ rems and proofs. So the emphasis is on problem solving rather than theory

CONTENT

1 Introduction -- 1.1 Equally Likely Outcomes -- 1.2 Interpretations -- 1.3 Distributions -- 1.4 Conditional Probability and Independence -- 1.5 Bayesโ{128}{153} Rule -- 1.6 Sequences of Events -- Summary -- Review Exercises -- 2 Repeated Trials and Sampling -- 2.1 The Binomial Distribution -- 2.2 Normal Approximation: Method -- 2.3 Normal Approximation: Derivation (Optional) -- 2.4 Poisson Approximation -- 2.5 Random Sampling -- Summary -- Review Exercises -- 3 Random Variables -- 3.1 Introduction -- 3.2 Expectation -- 3.3 Standard Deviation and Normal Approximation -- 3.4 Discrete Distributions -- 3.5 The Poisson Distribution -- 3.6 Symmetry (Optional) -- Summary -- Review Exercises -- 4 Continuous Distributions -- 4.1 Probability Densities -- 4.2 Exponential and Gamma Distributions -- 4.3 Hazard Rates (Optional) -- 4.4 Change of Variable -- 4.5 Cumulative Distribution Functions -- 4.6 Order Statistics (Optional) -- Summary -- Review Exercises -- 5 Continuous Joint Distributions -- 5.1 Uniform Distributions -- 5.2 Densities -- 5.3 Independent Normal Variables -- 5.4 Operations (Optional) -- Summary -- Review Exercises -- 6 Dependence -- 6.1 Conditional Distributions: Discrete Case -- 6.2 Conditional Expectation: Discrete Case -- 6.3 Conditioning: Density Case -- 6.4 Covariance and Correlation -- 6.5 Bivariate Normal -- Summary -- Review Exercises -- Distribution Summaries -- Discrete -- Continuous -- Beta -- Binomial -- Exponential -- Gamma -- Geometric and Negative Binomial -- Hypergeometrie -- Normal -- Poisson -- Uniform -- Examinations -- Solutions to Examinations -- Appendices -- 1 Counting -- 2 Sums -- 3 Calculus -- 4 Exponents and Logarithms -- 5 Normal Table -- Brief Solutions to Odd-Numbered Exercises

Mathematics
Probabilities
Statistics
Mathematics
Probability Theory and Stochastic Processes
Statistical Theory and Methods