Statistical Misconceptions
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Statistical Misconceptions
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Author : Schuyler Huck
language : en
Publisher: Routledge
Release Date : 2015-11-19
Statistical Misconceptions written by Schuyler Huck and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-19 with Psychology categories.
This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author’s accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists – examples and claimed prevalence Why the Misconception is Dangerous – consequence of having the misunderstanding Undoing the Misconception - how to think correctly about the concept Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception. The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook. An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.
Statistical Misconceptions
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Author : Schuyler W. Huck
language : en
Publisher: Taylor & Francis
Release Date : 2008-11-03
Statistical Misconceptions written by Schuyler W. Huck and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-11-03 with Education categories.
Brief and inexpensive, this engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Fun interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author’s accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists – examples and claimed prevalence Why the Misconception is Dangerous – consequence of having the misunderstanding Undoing the Misconception - how to think correctly about the concept Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception. The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook. Statistical Misconceptions is appropriate for courses taught in a variety of disciplines including psychology, medicine, education, nursing, business, and the social sciences. The book also will benefit independent researchers interested in undoing their statistical misconceptions.
Understanding Statistics And Statistical Myths
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Author : Kicab Castaneda-Mendez
language : en
Publisher: CRC Press
Release Date : 2015-11-18
Understanding Statistics And Statistical Myths written by Kicab Castaneda-Mendez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-18 with Business & Economics categories.
Addressing 30 statistical myths in the areas of data, estimation, measurement system analysis, capability, hypothesis testing, statistical inference, and control charts, this book explains how to understand statistics rather than how to do statistics. Every statistical myth listed in this book has been stated in course materials used by the author
Statistical Misconceptions
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Author : Schuyler W. Huck
language : en
Publisher: Routledge
Release Date : 2015-11-19
Statistical Misconceptions written by Schuyler W. Huck and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-19 with Psychology categories.
This engaging book helps readers identify and then discard 52 misconceptions about data and statistical summaries. The focus is on major concepts contained in typical undergraduate and graduate courses in statistics, research methods, or quantitative analysis. Interactive Internet exercises that further promote undoing the misconceptions are found on the book's website. The author’s accessible discussion of each misconception has five parts: The Misconception - a brief description of the misunderstanding Evidence that the Misconception Exists – examples and claimed prevalence Why the Misconception is Dangerous – consequence of having the misunderstanding Undoing the Misconception - how to think correctly about the concept Internet Assignment - an interactive activity to help readers gain a firm grasp of the statistical concept and overcome the misconception. The book's statistical misconceptions are grouped into 12 chapters that match the topics typically taught in introductory/intermediate courses. However, each of the 52 discussions is self-contained, thus allowing the misconceptions to be covered in any order without confusing the reader. Organized and presented in this manner, the book is an ideal supplement for any standard textbook. An ideal supplement for undergraduate and graduate courses in statistics, research methods, or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences. The book also appeals to independent researchers interested in undoing their statistical misconceptions.
Statistical And Methodological Myths And Urban Legends
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Author : Charles E. Lance
language : en
Publisher: Routledge
Release Date : 2010-10-18
Statistical And Methodological Myths And Urban Legends written by Charles E. Lance and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-18 with Business & Economics categories.
This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are sustained, in part, upon sound rationale and justification and, in part, upon unfounded lore. Some examples of these "methodological urban legends", as we refer to them in this book, are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can’t generalize these findings to the real world"; or (d) "your effect sizes are too low". Historically, there is a kernel of truth to most of these legends, but in many cases that truth has been long forgotten, ignored or embellished beyond recognition. This book examines several such legends. Each chapter is organized to address: (a) what the legend is that "we (almost) all know to be true"; (b) what the "kernel of truth" is to each legend; (c) what the myths are that have developed around this kernel of truth; and (d) what the state of the practice should be. This book meets an important need for the accumulation and integration of these methodological and statistical practices.
More Statistical And Methodological Myths And Urban Legends
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Author : Charles E. Lance
language : en
Publisher:
Release Date : 2015
More Statistical And Methodological Myths And Urban Legends written by Charles E. Lance and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with PSYCHOLOGY categories.
This book provides an up-to-date review of commonly undertaken methodological and statistical practices that are based partially in sound scientific rationale and partially in unfounded lore. Some examples of these "methodological urban legends" are characterized by manuscript critiques such as: (a) "your self-report measures suffer from common method bias"; (b) "your item-to-subject ratios are too low"; (c) "you can't generalize these findings to the real world"; or (d) "your effect sizes are too low." What do these critiques mean, and what is their historical basis? More Statistical and Methodological Myths and Urban Legends catalogs several of these quirky practices and outlines proper research techniques. Topics covered include sample size requirements, missing data bias in correlation matrices, negative wording in survey research, and much more.
Translating Statistics To Make Decisions
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Author : Victoria Cox
language : en
Publisher: Apress
Release Date : 2017-03-10
Translating Statistics To Make Decisions written by Victoria Cox and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-10 with Business & Economics categories.
Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians—and also statisticians who present statistical reports to non-statisticians—must avoid if statistical results are to be correctly used for evidence-based business decision making. Victoria Cox, senior statistician at the United Kingdom’s Defence Science and Technology Laboratory (Dstl), distills the lessons of her long experience presenting the actionable results of complex statistical studies to users of widely varying statistical sophistication across many disciplines: from scientists, engineers, analysts, and information technologists to executives, military personnel, project managers, and officials across UK government departments, industry, academia, and international partners. The author shows how faulty statistical reasoning often undermines the utility of statistical results even among those with advanced technical training. Translating Statistics teaches statistically naive readers enough about statistical questions, methods, models, assumptions, and statements that they will be able to extract the practical message from statistical reports and better constrain what conclusions cannot be made from the results. To non-statisticians with some statistical training, this book offers brush-ups, reminders, and tips for the proper use of statistics and solutions to common errors. To fellow statisticians, the author demonstrates how to present statistical output to non-statisticians to ensure that the statistical results are correctly understood and properly applied to real-world tasks and decisions. The book avoids algebra and proofs, but it does supply code written in R for those readers who are motivated to work out examples. Pointing along the way to instructive examples of statistics gone awry, Translating Statistics walks readers through the typical course of a statistical study, progressing from the experimental design stage through the data collection process, exploratory data analysis, descriptive statistics, uncertainty, hypothesis testing, statistical modelling and multivariate methods, to graphs suitable for final presentation. The steady focus throughout the book is on how to turn the mathematical artefacts and specialist jargon that are second nature to statisticians into plain English for corporate customers and stakeholders. The final chapter neatly summarizes the book’s lessons and insights for accurately communicating statistical reports to the non-statisticians who commission and act on them. What You'll Learn Recognize and avoid common errors and misconceptions that cause statistical studies to be misinterpreted and misused by non-statisticians in organizational settings Gain a practical understanding of the methods, processes, capabilities, and caveats of statistical studies to improve the application of statistical data to business decisions See how to code statistical solutions in R Who This Book Is For Non-statisticians—including both those with and without an introductory statistics course under their belts—who consume statistical reports in organizational settings, and statisticians who seek guidance for reporting statistical studies to non-statisticians in ways that will be accurately understood and will inform sound business and technical decisions
Ecrm2014 Proceedings Of The 13th European Conference On Research Methodology For Business And Management Studies
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Author : Dr Martin Rich
language : en
Publisher: Academic Conferences Limited
Release Date : 2014-06-16
Ecrm2014 Proceedings Of The 13th European Conference On Research Methodology For Business And Management Studies written by Dr Martin Rich and has been published by Academic Conferences Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-16 with Business & Economics categories.
Statistics Done Wrong
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Author : Alex Reinhart
language : en
Publisher: No Starch Press
Release Date : 2015-03-01
Statistics Done Wrong written by Alex Reinhart and has been published by No Starch Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-01 with Mathematics categories.
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.
Debunking Seven Terrorism Myths Using Statistics
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Author : Andre Python
language : en
Publisher: CRC Press
Release Date : 2020-07-10
Debunking Seven Terrorism Myths Using Statistics written by Andre Python and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-10 with Quantitative research categories.
What is terrorism? What can we learn and what cannot we learn from terrorism data? What are the perspectives and limitations of the analysis of terrorism data? Over the last decade, scholars have generated unprecedented insight from the statistical analysis of ever-growing databases on terrorism. Yet their findings have not reached the public. This book translates the current state of knowledge on global patterns of terrorism free of unnecessary jargon. Readers will be gradually introduced to statistical reasoning and tools applied to critically analyze terrorism data within a rigorous framework. Debunking Seven Terrorism Myths Using Statistics communicates evidence-based research work on terrorism to a general audience. It describes key statistics that provide an overview of the extent and magnitude of terrorist events perpetrated by actors independent of state governments across the world. The books brings a coherent and rigorous methodological framework to address issues stemming from the statistical analysis of terrorism data and its interpretations. Features Uses statistical reasoning to identify and address seven major misconceptions about terrorism. Discusses the implications of major issues about terrorism data on the interpretation of its statistical analysis. Gradually introduces the complexity of statistical methods to familiarize the non-statistician reader with important statistical concepts to analyze data. Use illustrated examples to help the reader develop a critical approach applied to the quantitative analysis of terrorism data. Includes chapters focusing on major aspects of terrorism: definitional issues, lethality, geography, temporal and spatial patterns, and the predictive ability of models.