Flaws and Fallacies in Statistical Thinking

Flaws and Fallacies in Statistical Thinking PDF Author: Stephen K. Campbell
Publisher: Courier Corporation
ISBN: 0486140512
Category : Mathematics
Languages : en
Pages : 210

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Book Description
Nontechnical survey helps improve ability to judge statistical evidence and to make better-informed decisions. Discusses common pitfalls: unrealistic estimates, improper comparisons, premature conclusions, and faulty thinking about probability. 1974 edition.

Flaws and Fallacies in Statistical Thinking

Flaws and Fallacies in Statistical Thinking PDF Author: Stephen K. Campbell
Publisher: Courier Corporation
ISBN: 0486140512
Category : Mathematics
Languages : en
Pages : 210

Get Book

Book Description
Nontechnical survey helps improve ability to judge statistical evidence and to make better-informed decisions. Discusses common pitfalls: unrealistic estimates, improper comparisons, premature conclusions, and faulty thinking about probability. 1974 edition.

Flaws and Fallacies in Statistical Thinking

Flaws and Fallacies in Statistical Thinking PDF Author: Stephen K. Campbell
Publisher:
ISBN:
Category :
Languages : en
Pages : 200

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Book Description


Mathematical Fallacies, Flaws, and Flimflam

Mathematical Fallacies, Flaws, and Flimflam PDF Author: Edward J. Barbeau
Publisher: American Mathematical Soc.
ISBN: 1614445184
Category : Mathematics
Languages : en
Pages : 167

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Book Description
A collection of mathematical errors, drawn from the work of students, textbooks, and the media, as well as from professional mathematicians themselves.

Bernoulli's Fallacy

Bernoulli's Fallacy PDF Author: Aubrey Clayton
Publisher: Columbia University Press
ISBN: 0231553358
Category : Mathematics
Languages : en
Pages : 641

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Book Description
There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences. The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations. Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. He highlights how influential nineteenth- and twentieth-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics. Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach—that is, to incorporate prior knowledge when reasoning with incomplete information—in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli’s Fallacy explains why something has gone wrong with how we use data—and how to fix it.

Statistics Done Wrong

Statistics Done Wrong PDF Author: Alex Reinhart
Publisher: No Starch Press
ISBN: 1593276206
Category : Mathematics
Languages : en
Pages : 177

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Book Description
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.

New Ecology for Education — Communication X Learning

New Ecology for Education — Communication X Learning PDF Author: Will W.K. Ma
Publisher: Springer
ISBN: 9811043469
Category : Education
Languages : en
Pages : 295

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Book Description
This book gathers the best papers from the HKAECT-AECT 2017 Summer International Research Symposium. Revealing the complex interactions between communication and learning, which are represented by the symbol “X” in the title, it provides a platform for knowledge exchange on the new ecology for education in the digital era. It also equips readers to handle complex issues in both communication and education, and clarifies the difference between practitioners and academics in communication and in education.

Keeping Up with the Quants

Keeping Up with the Quants PDF Author: Thomas H. Davenport
Publisher: Harvard Business Press
ISBN: 1422187268
Category : Business & Economics
Languages : en
Pages : 240

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Book Description
Why Everyone Needs Analytical Skills Welcome to the age of data. No matter your interests (sports, movies, politics), your industry (finance, marketing, technology, manufacturing), or the type of organization you work for (big company, nonprofit, small start-up)—your world is awash with data. As a successful manager today, you must be able to make sense of all this information. You need to be conversant with analytical terminology and methods and able to work with quantitative information. This book promises to become your “quantitative literacy" guide—helping you develop the analytical skills you need right now in order to summarize data, find the meaning in it, and extract its value. In Keeping Up with the Quants, authors, professors, and analytics experts Thomas Davenport and Jinho Kim offer practical tools to improve your understanding of data analytics and enhance your thinking and decision making. You’ll gain crucial skills, including: • How to formulate a hypothesis • How to gather and analyze relevant data • How to interpret and communicate analytical results • How to develop habits of quantitative thinking • How to deal effectively with the “quants” in your organization Big data and the analytics based on it promise to change virtually every industry and business function over the next decade. If you don’t have a business degree or if you aren’t comfortable with statistics and quantitative methods, this book is for you. Keeping Up with the Quants will give you the skills you need to master this new challenge—and gain a significant competitive edge.

Analytics and Big Data: The Davenport Collection (6 Items)

Analytics and Big Data: The Davenport Collection (6 Items) PDF Author: Thomas H. Davenport
Publisher: Harvard Business Review Press
ISBN: 1625277741
Category : Business & Economics
Languages : en
Pages : 961

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Book Description
The Analytics and Big Data collection offers a “greatest hits” digital compilation of ideas from world-renowned thought leader Thomas Davenport, who helped popularize the terms analytics and big data in the workplace. An agile and prolific thinker, Davenport has written or coauthored more than a dozen bestselling books. Several of these titles are offered together for the first time in this curated digital bundle, including: Big Data at Work, Competing on Analytics, Analytics at Work, and Keeping Up with the Quants. The collection also includes Davenport’s popular Harvard Business Review articles, “Data Scientist: The Sexiest Job of the 21st Century” (2012) and “Analytics 3.0” (2013). Combined, these works cover all the bases on analytics and big data: what each term means; the ramifications of each from a technical, consumer, and management perspective; and where each can have the biggest impact on your business. Whether you’re an executive, a manager, or a student wanting to learn more, Analytics and Big Data is the most comprehensive collection you’ll find on the ever-growing phenomenon of digital data and analysis—and how you can make this rising business trend work for you. Named one of the ten “Masters of the New Economy” by CIO magazine, Thomas Davenport has helped hundreds of companies revitalize their management practices. He combines his interests in research, teaching, and business management as the President’s Distinguished Professor of Information Technology & Management at Babson College. Davenport has also taught at Harvard Business School, the University of Chicago, Dartmouth’s Tuck School of Business, and the University of Texas at Austin and has directed research centers at Accenture, McKinsey & Company, Ernst & Young, and CSC. He is also an independent Senior Advisor to Deloitte Analytics.

Magnificent Mistakes in Mathematics

Magnificent Mistakes in Mathematics PDF Author: Alfred S. Posamentier
Publisher: Prometheus Books
ISBN: 1616147482
Category : Mathematics
Languages : en
Pages : 281

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Book Description
Two veteran math educators demonstrate how some "magnificent mistakes" had profound consequences for our understanding of mathematics' key concepts. In the nineteenth century, English mathematician William Shanks spent fifteen years calculating the value of pi, setting a record for the number of decimal places. Later, his calculation was reproduced using large wooden numerals to decorate the cupola of a hall in the Palais de la Découverte in Paris. However, in 1946, with the aid of a mechanical desk calculator that ran for seventy hours, it was discovered that there was a mistake in the 528th decimal place. Today, supercomputers have determined the value of pi to trillions of decimal places. This is just one of the amusing and intriguing stories about mistakes in mathematics in this layperson's guide to mathematical principles. In another example, the authors show that when we "prove" that every triangle is isosceles, we are violating a concept not even known to Euclid - that of "betweenness." And if we disregard the time-honored Pythagorean theorem, this is a misuse of the concept of infinity. Even using correct procedures can sometimes lead to absurd - but enlightening - results. Requiring no more than high-school-level math competency, this playful excursion through the nuances of math will give you a better grasp of this fundamental, all-important science.

Statistics and Probability in High School

Statistics and Probability in High School PDF Author: Carmen Batanero
Publisher: Springer
ISBN: 9463006249
Category : Education
Languages : en
Pages : 224

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Book Description
Statistics and probability are fascinating fields, tightly interwoven with the context of the problems which have to be modelled. The authors demonstrate how investigations and experiments provide promising teaching strategies to help high-school students acquire statistical and probabilistic literacy. In the first chapter the authors put into practice the following educational principles, reflecting their views of how these subjects should be taught: a focus on the most relevant ideas and postpone extensions to later stages; illustrating the complementary/dual nature of statistical and probabilistic reasoning; utilising the potential of technology and show its limits; and reflecting on the different levels of formalisation to meet the wide variety of students’ previous knowledge, abilities, and learning types. The remaining chapters deal with exploratory data analysis, modelling information by probabilities, exploring and modelling association, and with sampling and inference. Throughout the book, a modelling view of the concepts guides the presentation. In each chapter, the development of a cluster of fundamental ideas is centred around a statistical study or a real-world problem that leads to statistical questions requiring data in order to be answered. The concepts developed are designed to lead to meaningful solutions rather than remain abstract entities. For each cluster of ideas, the authors review the relevant research on misconceptions and synthesise the results of research in order to support teaching of statistics and probability in high school. What makes this book unique is its rich source of worked-through tasks and its focus on the interrelations between teaching and empirical research on understanding statistics and probability.