Wiley Series in Probability and Statistics: An Introduction to Probability and Statistics by Vijay K. Rohatgi download ebook DJV, TXT, FB2
9781118799642 English 111879964X A well-balanced introduction to probability theory and mathematical statistics Featuring a comprehensive update, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided into three parts, the Third Edition begins by presenting the fundamentals and foundations of probability. The second part addresses statistical inference, and the remaining chapters focus on special topics. Featuring a substantial revision to include recent developments, An Introduction to Probability and Statistics, Third Edition also 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 550 problems and answers to most problems, as well as 350 worked-out examples and 200 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., This Third Edition provides a solid and well-balancedintroduction to probability theory and mathematicalstatistics. The book is divided into three parts: Chapters1-6 form the core of probability fundamentals and foundations;Chapters 7-11 cover statistics inference; and the remainingchapters focus on special topics. For course sequences thatseparate probability and mathematics statistics, the first part ofthe book can be used for a course in probability theory, followedby a course in mathematical statistics based on the second part,and possibly, one or more chapters on special topics. Thebook contains over 550 problems, 350 worked-out examples, and 200side notes for reader reference. Numerous figures have beenadded to illustrate examples and proofs, and answers to selectproblems are now included. Many parts of the book haveundergone substantial rewriting, and the book has also beenreorganized. Chapters 6 and 7 have been interchanged to emphasizethe role of asymptotics in statistics, and the new Chapter 7contains all of the needed basic material on asymptotics. Chapter 6 also includes new material on resampling, specificallybootstrap. The new Further Results chapter include someestimation procedures such as M-estimatesand bootstrapping. A new chapter on regression analysishas also been added and contains sections on linear regression,multiple regression, subset regression, logistic regression, andPoisson regression.
9781118799642 English 111879964X A well-balanced introduction to probability theory and mathematical statistics Featuring a comprehensive update, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided into three parts, the Third Edition begins by presenting the fundamentals and foundations of probability. The second part addresses statistical inference, and the remaining chapters focus on special topics. Featuring a substantial revision to include recent developments, An Introduction to Probability and Statistics, Third Edition also 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 550 problems and answers to most problems, as well as 350 worked-out examples and 200 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., This Third Edition provides a solid and well-balancedintroduction to probability theory and mathematicalstatistics. The book is divided into three parts: Chapters1-6 form the core of probability fundamentals and foundations;Chapters 7-11 cover statistics inference; and the remainingchapters focus on special topics. For course sequences thatseparate probability and mathematics statistics, the first part ofthe book can be used for a course in probability theory, followedby a course in mathematical statistics based on the second part,and possibly, one or more chapters on special topics. Thebook contains over 550 problems, 350 worked-out examples, and 200side notes for reader reference. Numerous figures have beenadded to illustrate examples and proofs, and answers to selectproblems are now included. Many parts of the book haveundergone substantial rewriting, and the book has also beenreorganized. Chapters 6 and 7 have been interchanged to emphasizethe role of asymptotics in statistics, and the new Chapter 7contains all of the needed basic material on asymptotics. Chapter 6 also includes new material on resampling, specificallybootstrap. The new Further Results chapter include someestimation procedures such as M-estimatesand bootstrapping. A new chapter on regression analysishas also been added and contains sections on linear regression,multiple regression, subset regression, logistic regression, andPoisson regression.