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Author : Benjamin Yakir
Publisher : Unknown
Page : 324 pages
File Size : 51,5 Mb
Release : 2014-09-19
Category : Electronic
ISBN : 1502424665
Introduction to Statistical ThinkingBy Benjamin Yakir
Author : Benjamin Yakir
Publisher : Unknown
Page : 128 pages
File Size : 48,6 Mb
Release : 2010
Category : Applied mathematics
ISBN : OCLC:1266258417
Author : Michael Lavine
Publisher : Orange Grove Text Plus
Page : 0 pages
File Size : 55,5 Mb
Release : 2009-09-24
Category : Electronic
ISBN : 1616100486
This free PDF textbook is intended as an upper level undergraduate or introductory graduate textbook in statistical thinking. It is best suited to students with a good knowledge of calculus and the ability to think abstractly. The focus of the text is the ideas that statisticians care about as opposed to technical details of how to put those ideas into practice. Another unusual aspect is the use of statistical software as a pedagogical tool. That is, instead of viewing the computer merely as a convenient and accurate calculating device, the book uses computer calculation and simulation as another way of explaining and helping readers understand the underlying concepts. The book is written with the statistical language R embedded throughout. R software and accompanying manuals are available for free download from http: //www.r-project.or
Author : Leonard C. Onyiah
Publisher : Unknown
Page : 0 pages
File Size : 47,7 Mb
Release : 2011
Category : Statistics
ISBN : 0757589715
Author : Roger W. Hoerl,Ronald D. Snee
Publisher : John Wiley & Sons
Page : 640 pages
File Size : 54,5 Mb
Release : 2020-09-16
Category : Business & Economics
ISBN : 9781119605713
Apply statistics in business to achieve performance improvement Statistical Thinking: Improving Business Performance, 3rd Edition helps managers understand the role of statistics in implementing business improvements. It guides professionals who are learning statistics in order to improve performance in business and industry. It also helps graduate and undergraduate students understand the strategic value of data and statistics in arriving at real business solutions. Instruction in the book is based on principles of effective learning, established by educational and behavioral research. The authors cover both practical examples and underlying theory, both the big picture and necessary details. Readers gain a conceptual understanding and the ability to perform actionable analyses. They are introduced to data skills to improve business processes, including collecting the appropriate data, identifying existing data limitations, and analyzing data graphically. The authors also provide an in-depth look at JMP software, including its purpose, capabilities, and techniques for use. Updates to this edition include: A new chapter on data, assessing data pedigree (quality), and acquisition tools Discussion of the relationship between statistical thinking and data science Explanation of the proper role and interpretation of p-values (understanding of the dangers of “p-hacking”) Differentiation between practical and statistical significance Introduction of the emerging discipline of statistical engineering Explanation of the proper role of subject matter theory in order to identify causal relationships A holistic framework for variation that includes outliers, in addition to systematic and random variation Revised chapters based on significant teaching experience Content enhancements based on student input This book helps readers understand the role of statistics in business before they embark on learning statistical techniques.
Author : Michael A. Proschan
Publisher : CRC Press
Page : 276 pages
File Size : 46,7 Mb
Release : 2021-11-24
Category : Mathematics
ISBN : 9781351673105
Statistical Thinking in Clinical Trials combines a relatively small number of key statistical principles and several instructive clinical trials to gently guide the reader through the statistical thinking needed in clinical trials. Randomization is the cornerstone of clinical trials and randomization-based inference is the cornerstone of this book. Read this book to learn the elegance and simplicity of re-randomization tests as the basis for statistical inference (the analyze as you randomize principle) and see how re-randomization tests can save a trial that required an unplanned, mid-course design change. Other principles enable the reader to quickly and confidently check calculations without relying on computer programs. The `EZ’ principle says that a single sample size formula can be applied to a multitude of statistical tests. The `O minus E except after V’ principle provides a simple estimator of the log odds ratio that is ideally suited for stratified analysis with a binary outcome. The same principle can be used to estimate the log hazard ratio and facilitate stratified analysis in a survival setting. Learn these and other simple techniques that will make you an invaluable clinical trial statistician.
Author : Jim Albert,Ruud H. Koning
Publisher : CRC Press
Page : 312 pages
File Size : 55,9 Mb
Release : 2007-07-12
Category : Mathematics
ISBN : 9781584888697
Since the first athletic events found a fan base, sports and statistics have always maintained a tight and at times mythical relationship. As a way to relay the telling of a game's drama and attest to the prodigious powers of the heroes involved, those reporting on the games tallied up the numbers that they believe best described the action and bes
Author : Roger W. Hoerl,Ronald D. Snee
Publisher : John Wiley & Sons
Page : 544 pages
File Size : 47,5 Mb
Release : 2012-04-09
Category : Business & Economics
ISBN : 9781118236857
How statistical thinking and methodology can help you make crucial business decisions Straightforward and insightful, Statistical Thinking: Improving Business Performance, Second Edition, prepares you for business leadership by developing your capacity to apply statistical thinking to improve business processes. Unique and compelling, this book shows you how to derive actionable conclusions from data analysis, solve real problems, and improve real processes. Here, you'll discover how to implement statistical thinking and methodology in your work to improve business performance. Explores why statistical thinking is necessary and helpful Provides case studies that illustrate how to integrate several statistical tools into the decision-making process Facilitates and encourages an experiential learning environment to enable you to apply material to actual problems With an in-depth discussion of JMP® software, the new edition of this important book focuses on skills to improve business processes, including collecting data appropriate for a specified purpose, recognizing limitations in existing data, and understanding the limitations of statistical analyses.
Author : Richard McElreath
Publisher : CRC Press
Page : 488 pages
File Size : 43,5 Mb
Release : 2018-01-03
Category : Mathematics
ISBN : 9781315362618
Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.
Author : Andrew Zieffler
Publisher : Unknown
Page : 176 pages
File Size : 52,7 Mb
Release : 2012-08-29
Category : Mathematical statistics
ISBN : 0615691307
Learning statistics is sexy.Almost every person on earth will benefit from learning some foundational ideas of statistics. This is true because statistics forms the basis of our everyday world just as much as do science, technology, and politics. Google, Netflix, Twitter, Facebook, OKCupid, Match.com, Amazon, iTunes, and the Federal Government are just a handful of the companies and organizations that use statistics on a daily basis. Journalism, political science, biology, sociology, psychology, graphic design, economics, sports science, and dance are all disciplines that have made use of statistical methodology.The materials in this book will introduce you to the seminal ideas underlying the discipline of statistics. In addition, they have been designed with your learning in mind. As you engage in and use the skills, concepts and ideas introduced in the material, you will find yourself thinking about data and evidence in a different way.
Author : Yu-Kang Tu,Mark Gilthorpe
Publisher : CRC Press
Page : 231 pages
File Size : 53,7 Mb
Release : 2016-04-19
Category : Mathematics
ISBN : 9781420099928
While biomedical researchers may be able to follow instructions in the manuals accompanying the statistical software packages, they do not always have sufficient knowledge to choose the appropriate statistical methods and correctly interpret their results. Statistical Thinking in Epidemiology examines common methodological and statistical problems
Author : Dani Ben-Zvi,Joan Garfield
Publisher : Springer Science & Business Media
Page : 423 pages
File Size : 41,8 Mb
Release : 2006-02-23
Category : Mathematics
ISBN : 9781402022784
Unique in that it collects, presents, and synthesizes cutting edge research on different aspects of statistical reasoning and applies this research to the teaching of statistics to students at all educational levels, this volume will prove of great value to mathematics and statistics education researchers, statistics educators, statisticians, cognitive psychologists, mathematics teachers, mathematics and statistics curriculum developers, and quantitative literacy experts in education and government.
Author : Edwin Arthur Maxwell
Publisher : Prentice Hall
Page : 600 pages
File Size : 40,9 Mb
Release : 1983
Category : Mathematics
ISBN : UOM:39015051185000
Author : Frank E. Harrell
Publisher : Springer Science & Business Media
Page : 583 pages
File Size : 42,6 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9781475734621
Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".
Author : J. A. John,D. Whitaker
Publisher : CRC Press
Page : 408 pages
File Size : 51,9 Mb
Release : 2005-08-29
Category : Business & Economics
ISBN : 9781420057164
Business students need the ability to think statistically about how to deal with uncertainty and its effect on decision-making in business and management. Traditional statistics courses and textbooks tend to focus on probability, mathematical detail, and heavy computation, and thus fail to meet the needs of future managers. Statistical Thinking in
