Introduction To The Theory Of Statistical Inference
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Introduction To Statistical Inference
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Author : Jack C. Kiefer
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Introduction To Statistical Inference written by Jack C. Kiefer and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This book is based upon lecture notes developed by Jack Kiefer for a course in statistical inference he taught at Cornell University. The notes were distributed to the class in lieu of a textbook, and the problems were used for homework assignments. Relying only on modest prerequisites of probability theory and cal culus, Kiefer's approach to a first course in statistics is to present the central ideas of the modem mathematical theory with a minimum of fuss and formality. He is able to do this by using a rich mixture of examples, pictures, and math ematical derivations to complement a clear and logical discussion of the important ideas in plain English. The straightforwardness of Kiefer's presentation is remarkable in view of the sophistication and depth of his examination of the major theme: How should an intelligent person formulate a statistical problem and choose a statistical procedure to apply to it? Kiefer's view, in the same spirit as Neyman and Wald, is that one should try to assess the consequences of a statistical choice in some quan titative (frequentist) formulation and ought to choose a course of action that is verifiably optimal (or nearly so) without regard to the perceived "attractiveness" of certain dogmas and methods.
Essential Statistical Inference
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Author : Dennis D. Boos
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-02-06
Essential Statistical Inference written by Dennis D. Boos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-06 with Mathematics categories.
This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems. An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology. Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.
Probability Theory And Statistical Inference
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Author : Aris Spanos
language : en
Publisher: Cambridge University Press
Release Date : 2019-09-19
Probability Theory And Statistical Inference written by Aris Spanos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-19 with Business & Economics categories.
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Introduction To The Theory Of Statistical Inference
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Author : Hannelore Liero
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Introduction To The Theory Of Statistical Inference written by Hannelore Liero and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Mathematics categories.
Based on the authors' lecture notes, this text presents concise yet complete coverage of statistical inference theory, focusing on the fundamental classical principles. Unlike related textbooks, it combines the theoretical basis of statistical inference with a useful applied toolbox that includes linear models. Suitable for a second semester undergraduate course on statistical inference, the text offers proofs to support the mathematics and does not require any use of measure theory. It illustrates core concepts using cartoons and provides solutions to all examples and problems.
Principles Of Statistical Inference
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Author : D. R. Cox
language : en
Publisher: Cambridge University Press
Release Date : 2006-08-10
Principles Of Statistical Inference written by D. R. Cox and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-08-10 with Mathematics categories.
In this definitive book, D. R. Cox gives a comprehensive and balanced appraisal of statistical inference. He develops the key concepts, describing and comparing the main ideas and controversies over foundational issues that have been keenly argued for more than two-hundred years. Continuing a sixty-year career of major contributions to statistical thought, no one is better placed to give this much-needed account of the field. An appendix gives a more personal assessment of the merits of different ideas. The content ranges from the traditional to the contemporary. While specific applications are not treated, the book is strongly motivated by applications across the sciences and associated technologies. The mathematics is kept as elementary as feasible, though previous knowledge of statistics is assumed. The book will be valued by every user or student of statistics who is serious about understanding the uncertainty inherent in conclusions from statistical analyses.
All Of Statistics
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Author : Larry Wasserman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-11
All Of Statistics written by Larry Wasserman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-11 with Mathematics categories.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Introductory Statistical Inference
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Author : Nitis Mukhopadhyay
language : en
Publisher: CRC Press
Release Date : 2006-02-07
Introductory Statistical Inference written by Nitis Mukhopadhyay and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-07 with Mathematics categories.
Introductory Statistical Inference develops the concepts and intricacies of statistical inference. With a review of probability concepts, this book discusses topics such as sufficiency, ancillarity, point estimation, minimum variance estimation, confidence intervals, multiple comparisons, and large-sample inference. It introduces techniques of two-stage sampling, fitting a straight line to data, tests of hypotheses, nonparametric methods, and the bootstrap method. It also features worked examples of statistical principles as well as exercises with hints. This text is suited for courses in probability and statistical inference at the upper-level undergraduate and graduate levels.
A First Course In Statistical Inference
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Author : Jonathan Gillard
language : en
Publisher: Springer
Release Date : 2020-04-21
A First Course In Statistical Inference written by Jonathan Gillard and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-21 with Mathematics categories.
This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author’s extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics.
Statistical Inference For Everyone
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Author : Brian Blais
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2014-08-27
Statistical Inference For Everyone written by Brian Blais and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-27 with Mathematics categories.
Approaching an introductory statistical inference textbook in a novel way, this book is motivated by the perspective of "probability theory as logic". Targeted to the typical "Statistics 101" college student this book covers the topics typically treated in such a course - but from a fresh angle. This book walks through a simple introduction to probability, and then applies those principles to all problems of inference. Topics include hypothesis testing, data visualization, parameter inference, and model comparison. Statistical Inference for Everyone is freely available under the Creative Commons License, and includes a software library in Python for making calculations and visualizations straightforward.
Theory And Methods Of Statistics
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Author : P.K. Bhattacharya
language : en
Publisher: Academic Press
Release Date : 2016-05-27
Theory And Methods Of Statistics written by P.K. Bhattacharya and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-27 with Mathematics categories.
Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures.