Download or read book Common Errors in Statistics and How to Avoid Them written by Phillip I. Good and published by John Wiley & Sons. This book was released on 2006-06-23 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Common Errors in Statistics and How to Avoid Them written by Phillip I. Good and published by Wiley. This book was released on 2009-10-06 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Common Mistakes in Teaching Elementary Math And How to Avoid Them written by Fuchang Liu and published by Routledge. This book was released on 2017-03-27 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the most effective ways to teach elementary math, no matter how much experience you have with the subject. In this book, Fuchang Liu takes you through many common mistakes in math instruction and explains the misunderstandings behind them. He points out practices that should be avoided, helping you to adjust your lessons so that all students can achieve success. You’ll discover how to... - Increase your confidence with core math principles and reasoning - Set your students on the path toward eventually developing more complex math skills - Improve student achievement by approaching problems in logical yet creative ways - Overcome common challenges faced by students and teachers - Teach problem solving for different learning styles Every chapter reconsiders well-established ways of teaching all areas of elementary math, from addition and subtraction to statistics and graphs. Helpful examples and tips are scattered throughout the book, offering revisions to the way these topics are often presented in the classroom. Also included are group study ideas for principals and instructional coaches so your school or district can work on the book together. With this practical guide, you’ll be ready to help students truly develop their math understanding.

Download or read book Common Mistakes in Meta Analysis written by Michael Borenstein and published by . This book was released on 2019-08-15 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Statistical Rules of Thumb written by Gerald van Belle and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Avoiding Common Errors in the Emergency Department written by Amal Mattu and published by Lippincott Williams & Wilkins. This book was released on 2012-03-28 with total page 993 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pocket book succinctly describes 400 errors commonly made by attendings, residents, medical students, nurse practitioners, and physician assistants in the emergency department, and gives practical, easy-to-remember tips for avoiding these errors. The book can easily be read immediately before the start of a rotation or used for quick reference on call. Each error is described in a short clinical scenario, followed by a discussion of how and why the error occurs and tips on how to avoid or ameliorate problems. Areas covered include psychiatry, pediatrics, poisonings, cardiology, obstetrics and gynecology, trauma, general surgery, orthopedics, infectious diseases, gastroenterology, renal, anesthesia and airway management, urology, ENT, and oral and maxillofacial surgery.

Download or read book Statistics Done Wrong written by Alex Reinhart and published by No Starch Press. This book was released on 2015-03-01 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific progress depends on good research, and good research needs good statistics. But statistical analysis is tricky to get right, even for the best and brightest of us. You'd be surprised how many scientists are doing it wrong. Statistics Done Wrong is a pithy, essential guide to statistical blunders in modern science that will show you how to keep your research blunder-free. You'll examine embarrassing errors and omissions in recent research, learn about the misconceptions and scientific politics that allow these mistakes to happen, and begin your quest to reform the way you and your peers do statistics. You'll find advice on: –Asking the right question, designing the right experiment, choosing the right statistical analysis, and sticking to the plan –How to think about p values, significance, insignificance, confidence intervals, and regression –Choosing the right sample size and avoiding false positives –Reporting your analysis and publishing your data and source code –Procedures to follow, precautions to take, and analytical software that can help Scientists: Read this concise, powerful guide to help you produce statistically sound research. Statisticians: Give this book to everyone you know. The first step toward statistics done right is Statistics Done Wrong.

Download or read book Essential Biostatistics written by Harvey Motulsky and published by Oxford University Press. This book was released on 2016 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: With its engaging and conversational tone, Essential Biostatistics: A Nonmathematical Approach provides a clear introduction to statistics for students in a wide range of fields, and a concise statistics refresher for scientists and professionals who need to interpret statistical results. It explains the ideas behind statistics in nonmathematical terms, offers perspectives on how to interpret published statistical results, and points out common conceptual traps to avoid. It can be used as a stand-alone text or as a supplement to a traditional statistics textbook.

Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The Cambridge Handbook of Computing Education Research written by Sally A. Fincher and published by . This book was released on 2019-02-13 with total page 924 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an authoritative introduction to Computing Education research written by over 50 leading researchers from academia and the industry.

Download or read book Common Errors in Statistics written by Phillip I. Good and published by John Wiley & Sons. This book was released on 2003-08-29 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to choosing and using the right techniques High-speed computers and prepackaged statistical routines would seem to take much of the guesswork out of statistical analysis and lend its applications readily accessible to all. Yet, as Phillip Good and James Hardin persuasively argue, statistical software no more makes one a statistician than a scalpel makes one a surgeon. Choosing the proper technique and understanding the analytical context is of paramount importance to the proper application of statistics. The highly readable Common Errors in Statistics (and How to Avoid Them) provides both newly minted academics and professionals who use statistics in their work with a handy field guide to statistical problems and solutions. Good and Hardin begin their handbook by establishing a mathematically rigorous but readily accessible foundation for statistical procedures. They focus on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. A handy checklist is provided to summarize the necessary steps. Topics covered include: * 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 others Common Errors in Statistics (and How to Avoid Them) also contains reprints of classic articles from statistical literature to re-examine such bedrock subjects as linear regression, the analysis of variance, maximum likelihood, meta-analysis, and the bootstrap. With a final emphasis on finding solutions and on the great value of statistics when applied in the proper context, this book will prove eminently useful to students and professionals in the fields of research, industry, medicine, and government.

Download or read book Common Mistakes at IELTS Advanced written by Julie Moore and published by Cambridge English. This book was released on 2007-03-29 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: This invaluable little book highlights the real mistakes that students make in the exam - and shows how to avoid them. Based on analysis of thousands of exam scripts, each unit targets a key problem area. Clear explanations and exercises help students to use the language accurately. Regular tests offer students a further opportunity to check and consolidate what they have learnt. • Highlights common mistakes that learners really make. • Based on analysis of thousands of exam scripts. • Short, snappy explanations focus on key problem areas. • Includes exam-style exercises.

Download or read book Statistics for Health Care Professionals written by Ian Scott and published by SAGE. This book was released on 2005-02-09 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on quantative approaches to investigating problems, this title introduces the basics rules and principles of statistics, encouraging the reader to think critically about data analysis and research design, and how these factors can impact upon evidence-based practice.

Download or read book Avoiding Common Anesthesia Errors written by Catherine Marcucci and published by Lippincott Williams & Wilkins. This book was released on 2012-02-16 with total page 1086 pages. Available in PDF, EPUB and Kindle. Book excerpt: This pocket book succinctly describes 215 common, serious errors made by attendings, residents, fellows, CRNAs, and practicing anesthesiologists in the practice of anesthesia and offers practical, easy-to-remember tips for avoiding these errors. The book can easily be read immediately before the start of a rotation or used for quick reference. Each error is described in a quick-reading one-page entry that includes a brief clinical scenario, a short review of the relevant physiology and/or pharmacology, and tips on how to avoid or resolve the problem. Illustrations are included where appropriate. The book also includes important chapters on human factors, legal issues, CPT coding, and how to select a practice.

Download or read book How to Write Better Medical Papers written by Michael Hanna and published by Springer. This book was released on 2019-03-20 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book guides medical researchers through all stages of transforming their scientific data and ideas into a published paper. Many researchers in medicine, including the life sciences and health sciences, struggle to get their research written and published. Manuscripts are typically rejected and/or sent back for revisions several times before ever being published. One reason for this is that researchers have not received much instruction in the specific subjects and skills needed to write and publish scientific medical papers: research methodology, ethics, statistics, data visualization, writing, revising, and the practicalities of publishing. Instead of wasting the reader’s time discussing trivialities of punctuation, spelling, etc., this book tackles all the major scientific issues that routinely lead to manuscripts getting rejected from the journals. The section “Preparing” covers the range of methodological, ethical, and practical aspects that researchers need to address before starting to write their paper. The section “Analyzing” reviews commonplace problems in the statistical analysis and presentation, and how to resolve those problems. The section “Drafting” describes what to write in all the various parts of a paper (the Introduction, Methods, Results, Discussion, Abstract, etc.) The section “Revising” explains and illustrates how to improve the writing style of any manuscript. The section “Publishing” discusses how to navigate the peer review process and all other practical aspects of the publishing phase. This book draws on the author’s decade of experience as an independent medical writer and research consultant, but it is not written merely as the personal opinion of yet another expert. The entire book is grounded in the existing scientific and scholarly literature, with extensive references and a lengthy annotated bibliography, so readers can quickly obtain more information on any aspect they want. Thus this book provides a more evidence-based, scholarly account of how medical scientific papers should be written, in order to improve medical communication and accelerate scientific progress. After reading this entire book cover to cover, medical researchers will know how to write better quality medical papers, and they will be able to publish their work in better journals with less time and struggle. This book is essential reading for anyone conducting research in clinical medicine, life sciences, or health sciences.

Download or read book Naked Statistics Stripping the Dread from the Data written by Charles Wheelan and published by W. W. Norton & Company. This book was released on 2013-01-07 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: A New York Times bestseller "Brilliant, funny…the best math teacher you never had." —San Francisco Chronicle Once considered tedious, the field of statistics is rapidly evolving into a discipline Hal Varian, chief economist at Google, has actually called "sexy." From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you’ll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more. For those who slept through Stats 101, this book is a lifesaver. Wheelan strips away the arcane and technical details and focuses on the underlying intuition that drives statistical analysis. He clarifies key concepts such as inference, correlation, and regression analysis, reveals how biased or careless parties can manipulate or misrepresent data, and shows us how brilliant and creative researchers are exploiting the valuable data from natural experiments to tackle thorny questions. And in Wheelan’s trademark style, there’s not a dull page in sight. You’ll encounter clever Schlitz Beer marketers leveraging basic probability, an International Sausage Festival illuminating the tenets of the central limit theorem, and a head-scratching choice from the famous game show Let’s Make a Deal—and you’ll come away with insights each time. With the wit, accessibility, and sheer fun that turned Naked Economics into a bestseller, Wheelan defies the odds yet again by bringing another essential, formerly unglamorous discipline to life.

Download or read book Beyond Basic Statistics written by Kristin H. Jarman and published by John Wiley & Sons. This book was released on 2015-04-22 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Features basic statistical concepts as a tool for thinking critically, wading through large quantities of information, and answering practical, everyday questions Written in an engaging and inviting manner, Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know presents the more subjective side of statistics—the art of data analytics. Each chapter explores a different question using fun, common sense examples that illustrate the concepts, methods, and applications of statistical techniques. Without going into the specifics of theorems, propositions, or formulas, the book effectively demonstrates statistics as a useful problem-solving tool. In addition, the author demonstrates how statistics is a tool for thinking critically, wading through large volumes of information, and answering life’s important questions. Beyond Basic Statistics: Tips, Tricks, and Techniques Every Data Analyst Should Know also features: Plentiful examples throughout aimed to strengthen readers’ understanding of the statistical concepts and methods A step-by-step approach to elementary statistical topics such as sampling, hypothesis tests, outlier detection, normality tests, robust statistics, and multiple regression A case study in each chapter that illustrates the use of the presented techniques Highlights of well-known shortcomings that can lead to false conclusions An introduction to advanced techniques such as validation and bootstrapping Featuring examples that are engaging and non-application specific, the book appeals to a broad audience of students and professionals alike, specifically students of undergraduate statistics, managers, medical professionals, and anyone who has to make decisions based on raw data or compiled results.