Essentials of statistical inference. Young G.A., Smith R.L.

Essentials of statistical inference



Download Essentials of statistical inference



Essentials of statistical inference Young G.A., Smith R.L. ebook pdf
Publisher: CUP
Language: English
Page: 238
ISBN: 0521839718,

"This is a delightful book! It gives a well-written exposure to inference issues in statistics, very suitable for a first-year graduate course...The authors present the material in a very good pedagogical manner. The examples are excellent, and the exercises are very instructive...very much up to date and includes recent developments in the field."
MAA Reviews

"This is a solid book, ideal for advanced classes in the mathematical justification for statistical inference."
Journal of Recreational Mathematics

"I wish that I had had such a textbook during my student days...this new book presents the core ideas of statistical inference in the unifying framework of decision theory and includes a fruitful discussion of the different foundational standpoints (Bayesian, Fisherian and frequentist)...[it is] sufficiently precise to satisfy a mathematician and yet omitting too much technical detail that could hide the core of the ideas. Carefully selected examples from a rainbow of application areas such as baseball, coal-mining disasters or gene expression data make it even more enjoyable to read...this book is a very nice graduate level textbook."
Journal of the Royal Statistical Society

"[T]his book gives a clear and comprehensive account of the basic elements of statistical theory. It should make a good text for an advanced course on statistical inference...Students will find it informative and challenging."
ISI Short Book Reviews

"Essentials of Statistical Inference is a book worth having."
Jane L. Harvill, Baylor University for the Journal of The American Statistician

"The book is comprehensively written without dwelling in unnecessary details."
Iris Pigeot, Biometrics

"This book is very unique in that the authors present the foundations of all three schools of inference and produce the essential theoretical results in each approach. This text also contains a great bibliography that is partially annotated. Readers should pay attention to the annotations as they are very enlightening. This book could easily be used for a modern first graduate level course in mathematical statistics."
Michael R. Chernick, Significance This engaging textbook introduces the key ideas behind drawing formal inferences from data. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it is a concise account of the main approaches to inference, with particular emphasis on the contrasts between them. It is the first textbook to synthesize contemporary material on computational topics with basic mathematical theory. Numerous extended examples apply formal inference techniques to real data, while historical commentary sketches the development of the subject. Each chapter ends with a set of accessible problems.

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