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Author : Phillip I. Good
Publisher : Wiley-Interscience
Page : 128 pages
File Size : 55,9 Mb
Release : 2008-03-03
Category : Mathematics
ISBN : 0470383186
This set contains: 9780470383186 Common Errors in Statistics, Second Edition by Phillip I. Good and 9780471402275 Statistical Rules of Thumb by Gerald van Belle.
Author : Phillip I. Good,Gerald van Belle
Publisher : Wiley
Page : 545 pages
File Size : 44,8 Mb
Release : 2009-07-07
Category : Mathematics
ISBN : 0470556048
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-45798-6) and Statistical Rules of Thumb, Second Edition by Gerald van Belle (978-0-470-1448-0)
Author : Phillip I. Good,James W. Hardin
Publisher : John Wiley & Sons
Page : 268 pages
File Size : 43,8 Mb
Release : 2006-06-23
Category : Mathematics
ISBN : 9780471998518
Praise for the First Edition of Common Errors in Statistics " . . . let me recommend Common Errors to all those who interact with statistics, whatever their level of statistical understanding . . . " --Stats 40 " . . . written . . . for the people who define good practice rather than seek to emulate it." --Journal of Biopharmaceutical Statistics " . . . highly informative, enjoyable to read, and of potential use to a broad audience. It is a book that should be on the reference shelf of many statisticians and researchers." --The American Statistician " . . . I found this book the most easily readable statistics book ever. The credit for this certainly goes to Phillip Good." --E-STREAMS A tried-and-true guide to the proper application of statistics Now in a second edition, the highly readable Common Errors in Statistics (and How to Avoid Them) lays a mathematically rigorous and readily accessible foundation for understanding statistical procedures, problems, and solutions. This handy field guide analyzes common mistakes, debunks popular myths, and helps readers to choose the best and most effective statistical technique for each of their tasks. Written for both the newly minted academic and the professional who uses statistics in their work, the book covers creating a research plan, formulating a hypothesis, specifying sample size, checking assumptions, interpreting p-values and confidence intervals, building a model, data mining, Bayes' Theorem, the bootstrap, and many other topics. The Second Edition has been extensively revised to include: * Additional charts and graphs * Two new chapters, Interpreting Reports and Which Regression Method? * New sections on practical versus statistical significance and nonuniqueness in multivariate regression * Added material from the authors' online courses at statistics.com * New material on unbalanced designs, report interpretation, and alternative modeling methods With a final emphasis on both finding solutions and the great value of statistics when applied in the proper context, this book is eminently useful to students and professionals in the fields of research, industry, medicine, and government.
Author : Phillip I. Good,James W. Hardin
Publisher : Wiley-Interscience
Page : 0 pages
File Size : 40,5 Mb
Release : 2008-03-14
Category : Mathematics
ISBN : 0470388102
This set contains: 9780471794318 Common Errors in Statistics (and How to Avoid Them), 2nd Edition and 9780471715757 Introduction to Statistics Through Resampling Methods and R/S Plus?? both by Phillip I. Good and James W. Hardin.
Author : Gerald van Belle
Publisher : Wiley-Interscience
Page : 250 pages
File Size : 55,5 Mb
Release : 2002-03-22
Category : Mathematics
ISBN : UOM:49015003071827
This handbook intends to provide simple rules of thumb, widely applicable, robust, elegant, and that capture key statistical concepts. It provides a framework for considering statistical questions such as sample size and design of experiments.
Author : Gerald van Belle
Publisher : John Wiley & Sons
Page : 286 pages
File Size : 53,6 Mb
Release : 2011-09-20
Category : Mathematics
ISBN : 9781118210369
Praise for the First Edition: "For a beginner [this book] is a treasure trove; for an experienced person it can provide new ideas on how better to pursue the subject of applied statistics." —Journal of Quality Technology Sensibly organized for quick reference, Statistical Rules of Thumb, Second Edition compiles simple rules that are widely applicable, robust, and elegant, and each captures key statistical concepts. This unique guide to the use of statistics for designing, conducting, and analyzing research studies illustrates real-world statistical applications through examples from fields such as public health and environmental studies. Along with an insightful discussion of the reasoning behind every technique, this easy-to-use handbook also conveys the various possibilities statisticians must think of when designing and conducting a study or analyzing its data. Each chapter presents clearly defined rules related to inference, covariation, experimental design, consultation, and data representation, and each rule is organized and discussed under five succinct headings: introduction; statement and illustration of the rule; the derivation of the rule; a concluding discussion; and exploration of the concept's extensions. The author also introduces new rules of thumb for topics such as sample size for ratio analysis, absolute and relative risk, ANCOVA cautions, and dichotomization of continuous variables. Additional features of the Second Edition include: Additional rules on Bayesian topics New chapters on observational studies and Evidence-Based Medicine (EBM) Additional emphasis on variation and causation Updated material with new references, examples, and sources A related Web site provides a rich learning environment and contains additional rules, presentations by the author, and a message board where readers can share their own strategies and discoveries. Statistical Rules of Thumb, Second Edition is an ideal supplementary book for courses in experimental design and survey research methods at the upper-undergraduate and graduate levels. It also serves as an indispensable reference for statisticians, researchers, consultants, and scientists who would like to develop an understanding of the statistical foundations of their research efforts. A related website www.vanbelle.org provides additional rules, author presentations and more.
Author : Phillip I. Good,James W. Hardin
Publisher : John Wiley & Sons
Page : 231 pages
File Size : 46,6 Mb
Release : 2011-09-20
Category : Mathematics
ISBN : 9781118211274
Praise for the Second Edition "All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics ". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE ". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research. The Third Edition has been considerably expanded and revised to include: A new chapter on data quality assessment A new chapter on correlated data An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs Revamped exercises with a stronger emphasis on solutions An extended chapter on report preparation New sections on factor analysis as well as Poisson and negative binomial regression Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Author : Phillip I. Good
Publisher : Wiley
Page : 0 pages
File Size : 45,5 Mb
Release : 2009-07-07
Category : Mathematics
ISBN : 0470555793
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-45798-6) and Introduction to Statistics Through Resampling Methods and R/S-PLUS (978-0-471-71575-7)
Author : Jacob Cohen
Publisher : Routledge
Page : 625 pages
File Size : 55,7 Mb
Release : 2013-05-13
Category : Psychology
ISBN : 9781134742776
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author : Geoff Tennant
Publisher : Taylor & Francis
Page : 155 pages
File Size : 40,9 Mb
Release : 2017-07-05
Category : Business & Economics
ISBN : 9781351899819
This book comprehensively explores all of the underlying issues and elements which, together, constitute one of the most successful quality and management programmes upon which companies such as Motorola and GE base their success - Six Sigma. The author was directly involved in implementing Six Sigma quality principles and practices into a European division of GE Capital, deploying this initiative in an entirely service-oriented business for the first time. Drawing from and reflecting on his experience, Geoff Tennant develops a reasoned exploration of the benefits that Six Sigma offers to any organization and what can be expected from start to finish. He investigates the relationship between Six Sigma and quality, customer satisfaction, business processes and organizational structure, statistics and analysis and process improvement methodologies. Aimed at quality professionals, senior management and directors, as well as practitioners and students of Six Sigma, Six Sigma: SPC and TQM in Manufacturing and Services provides an in-depth but highly readable insight into the quality initiative that is certain to sweep European companies as it has large and global American corporations.
Author : Phillip I. Good
Publisher : Wiley
Page : 504 pages
File Size : 44,7 Mb
Release : 2009-07-07
Category : Mathematics
ISBN : 0470555890
This set features: Common Errors in Statistics (and How to Avoid Them), Third Edition by Phillip I. Good and James W. Hardin (978-0-470-48798-6)and Introduction to Statistics Through Resampling Methods and Microsoft Office Excel by Phillip I. Good (978-0-471-73191-7)
Author : Thomas D. Wickens
Publisher : Psychology Press
Page : 414 pages
File Size : 47,9 Mb
Release : 2014-02-25
Category : Psychology
ISBN : 9781317784784
This book describes the principles and techniques needed to analyze data that form a multiway contingency table. Wickens discusses the description of association in such data using log-linear and log-multiplicative models and defines how the presence of association is tested using hypotheses of independence and quasi-independence. The application of the procedures to real data is then detailed. This volume does not presuppose prior experience or knowledge of statistics beyond basic courses in fundamentals of probability and statistical inference. It serves as an ideal reference for professionals or as a textbook for graduate or advanced undergraduate students involved in statistics in the social sciences.
Author : Robert Nisbet,John Elder,Gary D. Miner
Publisher : Academic Press
Page : 859 pages
File Size : 46,7 Mb
Release : 2009-05-14
Category : Mathematics
ISBN : 9780080912035
The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation. The Handbook helps one discern the technical and business problem, understand the strengths and weaknesses of modern data mining algorithms, and employ the right statistical methods for practical application. Use this book to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques, and discusses their application to real problems, in ways accessible and beneficial to practitioners across industries - from science and engineering, to medicine, academia and commerce. This handbook brings together, in a single resource, all the information a beginner will need to understand the tools and issues in data mining to build successful data mining solutions. Written "By Practitioners for Practitioners" Non-technical explanations build understanding without jargon and equations Tutorials in numerous fields of study provide step-by-step instruction on how to use supplied tools to build models Practical advice from successful real-world implementations Includes extensive case studies, examples, MS PowerPoint slides and datasets CD-DVD with valuable fully-working 90-day software included: "Complete Data Miner - QC-Miner - Text Miner" bound with book
Author : Francis F. Pitard
Publisher : CRC Press
Page : 524 pages
File Size : 55,8 Mb
Release : 1993-08-03
Category : Mathematics
ISBN : 0849389178
Pierre Gy's Sampling Theory and Sampling Practice, Second Edition is a concise, step-by-step guide for process variability management and methods. Updated and expanded, this new edition provides a comprehensive study of heterogeneity, covering the basic principles of sampling theory and its various applications. It presents many practical examples to allow readers to select appropriate sampling protocols and assess the validity of sampling protocols from others. The variability of dynamic process streams using variography is discussed to help bridge sampling theory with statistical process control. Many descriptions of good sampling devices, as well as descriptions of poor ones, are featured to educate readers on what to look for when purchasing sampling systems. The book uses its accessible, tutorial style to focus on professional selection and use of methods. The book will be a valuable guide for mineral processing engineers; metallurgists; geologists; miners; chemists; environmental scientists; and practitioners in chemical, cement, steel, power generation, high performance materials, recycling, cereal, and pharmaceutical industries.
Author : John P. Hoffmann
Publisher : CRC Press
Page : 318 pages
File Size : 43,6 Mb
Release : 2021-09-09
Category : Mathematics
ISBN : 9781000438109
Research in social and behavioral sciences has benefited from linear regression models (LRMs) for decades to identify and understand the associations among a set of explanatory variables and an outcome variable. Linear Regression Models: Applications in R provides you with a comprehensive treatment of these models and indispensable guidance about how to estimate them using the R software environment. After furnishing some background material, the author explains how to estimate simple and multiple LRMs in R, including how to interpret their coefficients and understand their assumptions. Several chapters thoroughly describe these assumptions and explain how to determine whether they are satisfied and how to modify the regression model if they are not. The book also includes chapters on specifying the correct model, adjusting for measurement error, understanding the effects of influential observations, and using the model with multilevel data. The concluding chapter presents an alternative model—logistic regression—designed for binary or two-category outcome variables. The book includes appendices that discuss data management and missing data and provides simulations in R to test model assumptions. Features Furnishes a thorough introduction and detailed information about the linear regression model, including how to understand and interpret its results, test assumptions, and adapt the model when assumptions are not satisfied. Uses numerous graphs in R to illustrate the model’s results, assumptions, and other features. Does not assume a background in calculus or linear algebra, rather, an introductory statistics course and familiarity with elementary algebra are sufficient. Provides many examples using real-world datasets relevant to various academic disciplines. Fully integrates the R software environment in its numerous examples. The book is aimed primarily at advanced undergraduate and graduate students in social, behavioral, health sciences, and related disciplines, taking a first course in linear regression. It could also be used for self-study and would make an excellent reference for any researcher in these fields. The R code and detailed examples provided throughout the book equip the reader with an excellent set of tools for conducting research on numerous social and behavioral phenomena. John P. Hoffmann is a professor of sociology at Brigham Young University where he teaches research methods and applied statistics courses and conducts research on substance use and criminal behavior.