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Author: DONALD B. MACNAUGHTON Publisher: ISBN: Category : Languages : en Pages : 260
Book Description
From the preface The "threshold p-value"-the arbiter of statistical significance-has been a widely used gateway to believability and acceptance for publication in scientific research since 1925. However, a growing number of statisticians and other researchers say we should "move beyond" these ideas, suggesting we should greatly reduce our emphasis on them in scientific research. These authors are waging a well-intentioned, polite, and vigorous intellectual war on the ideas of a threshold p-value and statistical significance. This is a "good" war, because it forces important issues into the open, where they can be best understood and assessed. This book grew from a sense that the threshold-p-value gateway to publication of scientific research results is highly useful but is also widely misunderstood. The book presents, from first principles, a modern view of the role of the gateway, as used by some scientific journals. The ideas are explained in terms of the recent disagreement about them between the editorial in a Special Issue on Statistical Inference of the American Statistician and a subsequent editorial in the New England Journal of Medicine. The ideas are developed with almost no reference to mathematics. (A computer can do all the standard math if the user properly understands the key ideas.) The explanations are reinforced with practical examples. The discussion shows how the concept of a threshold-p-value gateway helps researchers and journal editors maximize the overall scientific, social, and commercial benefit of scientific research. The gateway does this by optimally balancing the rates of costly "false-positive" and "false-negative" errors in a scientific journal. The book also discusses the important related ideas of a relationship between variables, a scientific hypothesis test, and the "replication crisis" in some branches of scientific research. The body of the book, which covers the key ideas, is roughly 30% of the text. The remainder consists of 23 appendices that expand the ideas in useful directions. The material is aimed at scientific researchers, journal editors, science teachers, and science students in the biological, social, and physical sciences. It will also be of interest to statisticians, data scientists, philosophers of science, and lay readers seeking an integrated modern view of the high-level operation of the study of relationships between variables in scientific research. About the author Donald B. Macnaughton has been a statistical consultant for more than 40 years. He has managed the statistical aspects of research in the fields of experimental psychology, zoology, drug dependence, nursing, education, business, geography, physical education, and inmate rehabilitation, among others. His consulting work supports and informs his main interest, which is to read, understand, and write about the vital role of the field of statistics in scientific research.
Author: DONALD B. MACNAUGHTON Publisher: ISBN: Category : Languages : en Pages : 260
Book Description
From the preface The "threshold p-value"-the arbiter of statistical significance-has been a widely used gateway to believability and acceptance for publication in scientific research since 1925. However, a growing number of statisticians and other researchers say we should "move beyond" these ideas, suggesting we should greatly reduce our emphasis on them in scientific research. These authors are waging a well-intentioned, polite, and vigorous intellectual war on the ideas of a threshold p-value and statistical significance. This is a "good" war, because it forces important issues into the open, where they can be best understood and assessed. This book grew from a sense that the threshold-p-value gateway to publication of scientific research results is highly useful but is also widely misunderstood. The book presents, from first principles, a modern view of the role of the gateway, as used by some scientific journals. The ideas are explained in terms of the recent disagreement about them between the editorial in a Special Issue on Statistical Inference of the American Statistician and a subsequent editorial in the New England Journal of Medicine. The ideas are developed with almost no reference to mathematics. (A computer can do all the standard math if the user properly understands the key ideas.) The explanations are reinforced with practical examples. The discussion shows how the concept of a threshold-p-value gateway helps researchers and journal editors maximize the overall scientific, social, and commercial benefit of scientific research. The gateway does this by optimally balancing the rates of costly "false-positive" and "false-negative" errors in a scientific journal. The book also discusses the important related ideas of a relationship between variables, a scientific hypothesis test, and the "replication crisis" in some branches of scientific research. The body of the book, which covers the key ideas, is roughly 30% of the text. The remainder consists of 23 appendices that expand the ideas in useful directions. The material is aimed at scientific researchers, journal editors, science teachers, and science students in the biological, social, and physical sciences. It will also be of interest to statisticians, data scientists, philosophers of science, and lay readers seeking an integrated modern view of the high-level operation of the study of relationships between variables in scientific research. About the author Donald B. Macnaughton has been a statistical consultant for more than 40 years. He has managed the statistical aspects of research in the fields of experimental psychology, zoology, drug dependence, nursing, education, business, geography, physical education, and inmate rehabilitation, among others. His consulting work supports and informs his main interest, which is to read, understand, and write about the vital role of the field of statistics in scientific research.
Author: Deborah G. Mayo Publisher: Cambridge University Press ISBN: 1108563309 Category : Mathematics Languages : en Pages : 503
Book Description
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.
Author: Deirdre Nansen McCloskey Publisher: University of Michigan Press ISBN: 0472026100 Category : Business & Economics Languages : en Pages : 352
Book Description
“ McCloskey and Ziliak have been pushing this very elementary, very correct, very important argument through several articles over several years and for reasons I cannot fathom it is still resisted. If it takes a book to get it across, I hope this book will do it. It ought to.” — Thomas Schelling, Distinguished University Professor, School of Public Policy, University of Maryland, and 2005 Nobel Prize Laureate in Economics “ With humor, insight, piercing logic and a nod to history, Ziliak and McCloskey show how economists— and other scientists— suffer from a mass delusion about statistical analysis. The quest for statistical significance that pervades science today is a deeply flawed substitute for thoughtful analysis. . . . Yet few participants in the scientific bureaucracy have been willing to admit what Ziliak and McCloskey make clear: the emperor has no clothes.” — Kenneth Rothman, Professor of Epidemiology, Boston University School of Health The Cult of Statistical Significance shows, field by field, how “ statistical significance,” a technique that dominates many sciences, has been a huge mistake. The authors find that researchers in a broad spectrum of fields, from agronomy to zoology, employ “ testing” that doesn’ t test and “ estimating” that doesn’ t estimate. The facts will startle the outside reader: how could a group of brilliant scientists wander so far from scientific magnitudes? This study will encourage scientists who want to know how to get the statistical sciences back on track and fulfill their quantitative promise. The book shows for the first time how wide the disaster is, and how bad for science, and it traces the problem to its historical, sociological, and philosophical roots. Stephen T. Ziliak is the author or editor of many articles and two books. He currently lives in Chicago, where he is Professor of Economics at Roosevelt University. Deirdre N. McCloskey, Distinguished Professor of Economics, History, English, and Communication at the University of Illinois at Chicago, is the author of twenty books and three hundred scholarly articles. She has held Guggenheim and National Humanities Fellowships. She is best known for How to Be Human* Though an Economist (University of Michigan Press, 2000) and her most recent book, The Bourgeois Virtues: Ethics for an Age of Commerce (2006).
Author: John MaccInes Publisher: ISBN: 9781529754483 Category : Languages : en Pages :
Book Description
Social scientists often want to know if a finding is statistically significant, discuss the p-values or put confidence intervals around results. This course explains what these terms mean, how they are calculated, and how their origin lies in the way we use samples to measure and investigate people, organizations and societies. By the end of this course, learners will be able to: Understand the definition of and factors involved in establishing statistical significance Recognize the importance of inference and how we gain information about populations from samples Define, interpret, and calculate normal distribution Establish the validity of sample estimates through calculating and interpreting the standard error Use confidence intervals to identify a range of samples that will include the population parameter under investigation Define and calculate the p-value in order to interpret the statistical significance of your null hypothesis Recognize and evaluate what the p-value can tell us about our research.
Author: Jacob Cohen Publisher: Routledge ISBN: 1134742770 Category : Psychology Languages : en Pages : 625
Book Description
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
Author: Joseph Gfroerer Publisher: Cambridge University Press ISBN: 1108651623 Category : Social Science Languages : en Pages : 544
Book Description
The primary data driver behind US drug policy is the National Survey on Drug Use and Health. This insider history traces the evolution of the survey and how the survey has interacted with the political and social climate of the country, from its origins during the Vietnam War to its role in the war on drugs. The book includes first-hand accounts that explain how the data was used and misused by political leaders, why changes were made in the survey design, and what challenges researchers faced in communicating statistical principles to policymakers and leaders. It also makes recommendations for managing survey data collection and reporting in the context of political pressures and technological advances. Survey research students and practitioners will learn practical lessons about questionnaire design, mode effects, sampling, nonresponse, weighting, editing, imputation, statistical significance, and confidentiality. The book also includes common-language explanations of key terms and processes to help data users understand the point of view of survey statisticians.
Author: David Spiegelhalter Publisher: Penguin UK ISBN: 0241258758 Category : Mathematics Languages : en Pages : 269
Book Description
'A statistical national treasure' Jeremy Vine, BBC Radio 2 'Required reading for all politicians, journalists, medics and anyone who tries to influence people (or is influenced) by statistics. A tour de force' Popular Science Do busier hospitals have higher survival rates? How many trees are there on the planet? Why do old men have big ears? David Spiegelhalter reveals the answers to these and many other questions - questions that can only be addressed using statistical science. Statistics has played a leading role in our scientific understanding of the world for centuries, yet we are all familiar with the way statistical claims can be sensationalised, particularly in the media. In the age of big data, as data science becomes established as a discipline, a basic grasp of statistical literacy is more important than ever. In The Art of Statistics, David Spiegelhalter guides the reader through the essential principles we need in order to derive knowledge from data. Drawing on real world problems to introduce conceptual issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether serial killer Harold Shipman could have been caught earlier, and if screening for ovarian cancer is beneficial. 'Shines a light on how we can use the ever-growing deluge of data to improve our understanding of the world' Nature
Author: Giulio D'Agostini Publisher: World Scientific ISBN: 9814486094 Category : Mathematics Languages : en Pages : 352
Book Description
This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The basic ideas of this “new” approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide — under well-defined assumptions! — with “standard” methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework. Contents: Critical Review and Outline of the Bayesian Alternative:Uncertainty in Physics and the Usual Methods of Handling ItA Probabilistic Theory of Measurement UncertaintyA Bayesian Primer:Subjective Probability and Bayes' TheoremProbability Distributions (A Concise Reminder)Bayesian Inference of Continuous QuantitiesGaussian LikelihoodCounting ExperimentsBypassing Bayes' Theorem for Routine ApplicationsBayesian UnfoldingFurther Comments, Examples and Applications:Miscellanea on General Issues in Probability and InferenceCombination of Experimental Results: A Closer LookAsymmetric Uncertainties and Nonlinear PropagationWhich Priors for Frontier Physics?Conclusion:Conclusions and Bibliography Readership: Graduate students and researchers interested in probability and statistics and their applications in science, particularly the evaluation of uncertainty in measurements. Keywords:Probability;Bayesian Statistics;Error Theory;Measurement Uncertainty;MetrologyReviews:“… statistics textbooks must take seriously the need to teach the foundations of statistical reasoning from the beginning … D'Agostini's new book does this admirably, building an edifice of Bayesian statistical reasoning in the physical sciences on solid foundations.”Journal of the American Statistical Association
Author: Harald B. Teicher Publisher: Labcoat Guide to Crop Protecti ISBN: 9781798120903 Category : Science Languages : en Pages : 184
Book Description
Are you a student, researcher or science leader looking for an overview of the essential principles of Biostatistics? This book is an easily accessible primer for scientists and research workers not trained in mathematical theory, but who have previously followed a course in Biological Statistics. This book provides a readily accessible overview on how to plan, implement and analyse experiments without access to a dedicated staff of statisticians. Guide To Essential Biostatistics contains few calculations (the "how" of Biostatistics) but instead provides a plain-English overview of the "why" - what is it the numbers are telling us, and how can we use this to plan trials, understand our data and make decisions. Designed to fit in a lab coat pocket for easy access, this GUIDE TO ESSENTIAL BIOSTATISTICS compiles some of the most-used biostatistical techniques, approximations and rules-of-thumb used in the design and analysis of biological experiments. The author has a 20+ year R&D background in the Corporate & Academic AgChem & BioScience community, and provides strategic and technical expertise to start-ups and corporations developing chemical and biological crop protection products. Buy this book to obtain an overview of essential aspects of Biostatistics! By purchasing the print edition of this book on AMAZON, you are eligible for a FREE download of the eBook version, providing access to high-resolution, zoomable color images.
Author: Charles Wheelan Publisher: W. W. Norton & Company ISBN: 0393089827 Category : Mathematics Languages : en Pages : 320
Book Description
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.
Author: DONALD B. MACNAUGHTON
Author: DONALD B. MACNAUGHTON
Author: Deborah G. Mayo
Author: Deirdre Nansen McCloskey
Author: John MaccInes
Author: Jacob Cohen
Author: Joseph Gfroerer
Author: David Spiegelhalter
Author: Giulio D'Agostini
Author: Harald B. Teicher
Author: Charles Wheelan