This book is organized into two sections encompassing nine chapters. The first part deals with the concept and elementary properties of probability space, and random variables and their probability distributions. The second part explores pertinent topics in mathematical statistics, including the concept of sampling, estimation, and hypotheses testing. This book is intended primarily for undergraduate statistics students.
Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics Additional topical coverage on bootstrapping, estimation procedures, and resampling Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals Over problems and answers to most problems, as well as worked out examples and remarks Numerous figures to further illustrate examples and proofs throughout An Introduction to Probability and Statistics, Third Edition is an ideal reference and resource for scientists and engineers in the fields of statistics, mathematics, physics, industrial management, and engineering.
The book is also an excellent text for upper-undergraduate and graduate-level students majoring in probability and statistics. Exercises with some solutions. Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising.
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Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability.
The second part addresses statistical inference, and the remainingchapters focus on special topics. A new section on regression analysis to include multiple regression, logistic regression, and Poisson regression. A reorganized chapter on large sample theory to emphasize the growing role of asymptotic statistics. Discussions on invariance, ancillary statistics, conjugate prior distributions, and invariant confidence intervals. Over problems and answers to most problems, as well as worked out examples and remarks.
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