Computer Age Statistical Inference Student Edition PDF Download

Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Computer Age Statistical Inference Student Edition PDF full book. Access full book title Computer Age Statistical Inference Student Edition.

Computer Age Statistical Inference, Student Edition

Computer Age Statistical Inference, Student Edition
Author: Bradley Efron
Publisher: Cambridge University Press
Total Pages: 514
Release: 2021-06-17
Genre: Mathematics
ISBN: 1108915876

Download Computer Age Statistical Inference, Student Edition Book in PDF, ePub and Kindle

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov Chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. Each chapter ends with class-tested exercises, and the book concludes with speculation on the future direction of statistics and data science.


Computer Age Statistical Inference

Computer Age Statistical Inference
Author: Bradley Efron
Publisher: Cambridge University Press
Total Pages: 496
Release: 2016-07-21
Genre: Mathematics
ISBN: 1108107958

Download Computer Age Statistical Inference Book in PDF, ePub and Kindle

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.


Computer Age Statistical Inference, Student Edition

Computer Age Statistical Inference, Student Edition
Author: Bradley Efron
Publisher: Cambridge University Press
Total Pages: 513
Release: 2021-06-17
Genre: Computers
ISBN: 1108823416

Download Computer Age Statistical Inference, Student Edition Book in PDF, ePub and Kindle

Now in paperback and fortified with exercises, this brilliant, enjoyable text demystifies data science, statistics and machine learning.


Statistical Inference

Statistical Inference
Author: George Casella
Publisher: CRC Press
Total Pages: 1746
Release: 2024-05-23
Genre: Mathematics
ISBN: 1040024025

Download Statistical Inference Book in PDF, ePub and Kindle

This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.


Parametric Statistical Inference

Parametric Statistical Inference
Author: James K. Lindsey
Publisher: Oxford University Press
Total Pages: 512
Release: 1996
Genre: Mathematics
ISBN: 9780198523598

Download Parametric Statistical Inference Book in PDF, ePub and Kindle

Two unifying components of statistics are the likelihood function and the exponential family. These are brought together for the first time as the central themes in this book on statistical inference, written for advanced undergraduate and graduate students in mathematical statistics.


Large-Scale Inference

Large-Scale Inference
Author: Bradley Efron
Publisher: Cambridge University Press
Total Pages:
Release: 2012-11-29
Genre: Mathematics
ISBN: 1139492136

Download Large-Scale Inference Book in PDF, ePub and Kindle

We live in a new age for statistical inference, where modern scientific technology such as microarrays and fMRI machines routinely produce thousands and sometimes millions of parallel data sets, each with its own estimation or testing problem. Doing thousands of problems at once is more than repeated application of classical methods. Taking an empirical Bayes approach, Bradley Efron, inventor of the bootstrap, shows how information accrues across problems in a way that combines Bayesian and frequentist ideas. Estimation, testing and prediction blend in this framework, producing opportunities for new methodologies of increased power. New difficulties also arise, easily leading to flawed inferences. This book takes a careful look at both the promise and pitfalls of large-scale statistical inference, with particular attention to false discovery rates, the most successful of the new statistical techniques. Emphasis is on the inferential ideas underlying technical developments, illustrated using a large number of real examples.


Aspects of Statistical Inference

Aspects of Statistical Inference
Author: A. H. Welsh
Publisher: John Wiley & Sons
Total Pages: 480
Release: 2011-09-15
Genre: Mathematics
ISBN: 1118165438

Download Aspects of Statistical Inference Book in PDF, ePub and Kindle

Relevant, concrete, and thorough--the essential data-based text onstatistical inference The ability to formulate abstract concepts and draw conclusionsfrom data is fundamental to mastering statistics. Aspects ofStatistical Inference equips advanced undergraduate and graduatestudents with a comprehensive grounding in statistical inference,including nonstandard topics such as robustness, randomization, andfinite population inference. A. H. Welsh goes beyond the standard texts and expertly synthesizesbroad, critical theory with concrete data and relevant topics. Thetext follows a historical framework, uses real-data sets andstatistical graphics, and treats multiparameter problems, yet isultimately about the concepts themselves. Written with clarity and depth, Aspects of Statistical Inference: * Provides a theoretical and historical grounding in statisticalinference that considers Bayesian, fiducial, likelihood, andfrequentist approaches * Illustrates methods with real-data sets on diabetic retinopathy,the pharmacological effects of caffeine, stellar velocity, andindustrial experiments * Considers multiparameter problems * Develops large sample approximations and shows how to use them * Presents the philosophy and application of robustness theory * Highlights the central role of randomization in statistics * Uses simple proofs to illuminate foundational concepts * Contains an appendix of useful facts concerning expansions,matrices, integrals, and distribution theory Here is the ultimate data-based text for comparing and presentingthe latest approaches to statistical inference.


Order Statistics & Inference

Order Statistics & Inference
Author: Narayanaswamy Balakrishnan
Publisher: Elsevier
Total Pages: 399
Release: 2014-06-28
Genre: Mathematics
ISBN: 1483297497

Download Order Statistics & Inference Book in PDF, ePub and Kindle

The literature on order statistics and inferenc eis quite extensive and covers a large number of fields ,but most of it is dispersed throughout numerous publications. This volume is the consolidtion of the most important results and places an emphasis on estimation. Both theoretical and computational procedures are presented to meet the needs of researchers, professionals, and students. The methods of estimation discussed are well-illustrated with numerous practical examples from both the physical and life sciences, including sociology,psychology,a nd electrical and chemical engineering. A complete, comprehensive bibliography is included so the book can be used both aas a text and reference.


An Introduction to the Bootstrap

An Introduction to the Bootstrap
Author: Bradley Efron
Publisher: CRC Press
Total Pages: 456
Release: 1994-05-15
Genre: Mathematics
ISBN: 9780412042317

Download An Introduction to the Bootstrap Book in PDF, ePub and Kindle

Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.


Statistical Inference as Severe Testing

Statistical Inference as Severe Testing
Author: Deborah G. Mayo
Publisher: Cambridge University Press
Total Pages: 503
Release: 2018-09-20
Genre: Mathematics
ISBN: 1108563309

Download Statistical Inference as Severe Testing Book in PDF, ePub and Kindle

Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.