-PDF Download- Statistical Misconceptions EBOOK

Statistical Misconceptions

Author: Schuyler Huck

Publisher: Routledge

Published: 2015-11-19

Total Pages: 321

ISBN-13: 1317311566

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

Author: Charles E. Lance

Publisher: Routledge

Published: 2010-10-18

Total Pages: 433

ISBN-13: 1135269661

DOWNLOAD EBOOK →

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.

Statistical Misconceptions

Author: Schuyler W. Huck

Publisher: Taylor & Francis

Published: 2008-11-03

Total Pages: 313

ISBN-13: 1135596352

DOWNLOAD EBOOK →

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.

Statistical Misconceptions

Author: Schuyler W. Huck

Publisher: Routledge

Published: 2015-11-19

Total Pages: 228

ISBN-13: 1317311558

DOWNLOAD EBOOK →

Statistics Done Wrong

Author: Alex Reinhart

Publisher: No Starch Press

Published: 2015-03-01

Total Pages: 177

ISBN-13: 1593276206

DOWNLOAD EBOOK →

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.

Understanding Statistics and Statistical Myths

Author: Kicab Castaneda-Mendez

Publisher: CRC Press

Published: 2015-11-18

Total Pages: 585

ISBN-13: 1498727468

DOWNLOAD EBOOK →

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

The Teaching and Learning of Statistics

Author: Dani Ben-Zvi

Publisher: Springer

Published: 2015-12-24

Total Pages: 334

ISBN-13: 3319234706

DOWNLOAD EBOOK →

This book presents the breadth and diversity of empirical and practical work done on statistics education around the world. A wide range of methods are used to respond to the research questions that form it's base. Case studies of single students or teachers aimed at understanding reasoning processes, large-scale experimental studies attempting to generalize trends in the teaching and learning of statistics are both employed. Various epistemological stances are described and utilized. The teaching and learning of statistics is presented in multiple contexts in the book. These include designed settings for young children, students in formal schooling, tertiary level students, vocational schools, and teacher professional development. A diversity is evident also in the choices of what to teach (curriculum), when to teach (learning trajectory), how to teach (pedagogy), how to demonstrate evidence of learning (assessment) and what challenges teachers and students face when they solve statistical problems (reasoning and thinking).

Debunking Seven Terrorism Myths Using Statistics

Author: Andre Python

Publisher: CRC Press

Published: 2020-07-10

Total Pages: 142

ISBN-13: 9780367472283

DOWNLOAD EBOOK →

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.

ECRM2014-Proceedings of the 13th European Conference on Research Methodology for Business and Management Studies

Author: Dr Martin Rich

Publisher: Academic Conferences Limited

Published: 2014-06-16

Total Pages: 497

ISBN-13: 1909507571

DOWNLOAD EBOOK →

Statistical Inference as Severe Testing

Author: Deborah G. Mayo

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 503

ISBN-13: 1108563309

DOWNLOAD EBOOK →

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.