What is a P-value Anyway?

What is a P-value Anyway?

Author: Andrew Vickers

Publisher: Pearson

Published: 2010

Total Pages: 232

ISBN-13:

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What is a p-value Anyway? offers a fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day. Describing data; Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making; Some common statistical errors, and what they teach us For all readers interested in statistics.


How to Lie with Statistics

How to Lie with Statistics

Author: Darrell Huff

Publisher: W. W. Norton & Company

Published: 2010-12-07

Total Pages: 144

ISBN-13: 0393070875

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If you want to outsmart a crook, learn his tricks—Darrell Huff explains exactly how in the classic How to Lie with Statistics. From distorted graphs and biased samples to misleading averages, there are countless statistical dodges that lend cover to anyone with an ax to grind or a product to sell. With abundant examples and illustrations, Darrell Huff’s lively and engaging primer clarifies the basic principles of statistics and explains how they’re used to present information in honest and not-so-honest ways. Now even more indispensable in our data-driven world than it was when first published, How to Lie with Statistics is the book that generations of readers have relied on to keep from being fooled.


The Meaning of Science

The Meaning of Science

Author: Tim Lewens

Publisher: Basic Books

Published: 2016-01-26

Total Pages: 176

ISBN-13: 0465097499

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A philosopher of science examines the biggest ethical and moral issues in science today, and explains why they matter for all of us -- scientist and layman alike Science has produced explanations for everything from the mechanisms of insect navigation to the formation of black holes and the workings of black markets. But how much can we trust science, and can we actually know the world through it? How does science work and how does it fail? And how can the work of scientists help -- or hurt -- everyday people? These are not questions that science can answer on its own. This is where philosophy of science comes in. Studying science without philosophy is, to quote Einstein, to be "like somebody who has seen thousands of trees but has never seen a forest." Cambridge philosopher Tim Lewens shows us the forest. He walks us through the theories of seminal philosophers of science Karl Popper and Thomas Kuhn and considers what science is, how far it can and should reach, and how we can determine the nature of its truths and myths. These philosophical issues have consequences that stretch far beyond the laboratory. For instance: What role should scientists have in policy discussions on environmental issues such as fracking? What are the biases at play in the search for a biological function of the female orgasm? If brain scans can be used to demonstrate that a decision was made several seconds before a person actually makes a conscious choice, what does that tell us about the possibility of free will? By examining science through this philosophical lens, Lewens reveals what physics can teach us about reality, what biology teaches us about human nature, and what cognitive science teaches us about human freedom. A masterful analysis of the biggest scientific and ethical issues of our age, The Meaning of Science forces us to confront the practical, personal, and political purposes of science -- and why it matters to all of us.


Statistics in Corpus Linguistics

Statistics in Corpus Linguistics

Author: Vaclav Brezina

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 317

ISBN-13: 1107125707

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A comprehensive and accessible introduction to statistics in corpus linguistics, covering multiple techniques of quantitative language analysis and data visualisation.


Corrupt Research

Corrupt Research

Author: Raymond Hubbard

Publisher: SAGE Publications

Published: 2015-07-01

Total Pages: 255

ISBN-13: 1506305377

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Addressing the immensely important topic of research credibility, Raymond Hubbard’s groundbreaking work proposes that we must treat such information with a healthy dose of skepticism. This book argues that the dominant model of knowledge procurement subscribed to in these areas—the significant difference paradigm—is philosophically suspect, methodologically impaired, and statistically broken. Hubbard introduces a more accurate, alternative framework—the significant sameness paradigm—for developing scientific knowledge. The majority of the book comprises a head-to-head comparison of the "significant difference" versus "significant sameness" conceptions of science across philosophical, methodological, and statistical perspectives.


Teaching Statistics

Teaching Statistics

Author: Andrew Gelman

Publisher: OUP Oxford

Published: 2002-08-08

Total Pages: 353

ISBN-13: 0191606995

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Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part II gives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.


Statistics Done Wrong

Statistics Done Wrong

Author: Alex Reinhart

Publisher: No Starch Press

Published: 2015-03-01

Total Pages: 177

ISBN-13: 1593276206

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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.


Statistical Inference as Severe Testing

Statistical Inference as Severe Testing

Author: Deborah G. Mayo

Publisher: Cambridge University Press

Published: 2018-09-20

Total Pages: 503

ISBN-13: 1108563309

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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.


Quantitative Social Science

Quantitative Social Science

Author: Kosuke Imai

Publisher: Princeton University Press

Published: 2021-03-16

Total Pages: 464

ISBN-13: 0691191093

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"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--