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Statistical Significance
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Book Synopsis The Cult of Statistical Significance by : Stephen Thomas Ziliak
Download or read book The Cult of Statistical Significance written by Stephen Thomas Ziliak and published by University of Michigan Press. This book was released on 2008-02-19 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: How the most important statistical method used in many of the sciences doesn't pass the test for basic common sense
Book Synopsis Communication Research Statistics by : John C. Reinard
Download or read book Communication Research Statistics written by John C. Reinard and published by SAGE Publications. This book was released on 2006-04-20 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: "While most books on statistics seem to be written as though targeting other statistics professors, John Reinard′s Communication Research Statistics is especially impressive because it is clearly intended for the student reader, filled with unusually clear explanations and with illustrations on the use of SPSS. I enjoyed reading this lucid, student-friendly book and expect students will benefit enormously from its content and presentation. Well done!" --John C. Pollock, The College of New Jersey Written in an accessible style using straightforward and direct language, Communication Research Statistics guides students through the statistics actually used in most empirical research undertaken in communication studies. This introductory textbook is the only work in communication that includes details on statistical analysis of data with a full set of data analysis instructions based on SPSS 12 and Excel XP. Key Features: Emphasizes basic and introductory statistical thinking: The basic needs of novice researchers and students are addressed, while underscoring the foundational elements of statistical analyses in research. Students learn how statistics are used to provide evidence for research arguments and how to evaluate such evidence for themselves. Prepares students to use statistics: Students are encouraged to use statistics as they encounter and evaluate quantitative research. The book details how statistics can be understood by developing actual skills to carry out rudimentary work. Examples are drawn from mass communication, speech communication, and communication disorders. Incorporates SPSS 12 and Excel: A distinguishing feature is the inclusion of coverage of data analysis by use of SPSS 12 and by Excel. Information on the use of major computer software is designed to let students use such tools immediately. Companion Web Site! A dedicated Web site includes a glossary, data sets, chapter summaries, additional readings, links to other useful sites, selected "calculators" for computation of related statistics, additional macros for selected statistics using Excel and SPSS, and extra chapters on multiple discriminant analysis and loglinear analysis. Intended Audience: Ideal for undergraduate and graduate courses in Communication Research Statistics or Methods; also relevant for many Research Methods courses across the social sciences
Book Synopsis Statistical Significance Testing for Natural Language Processing by : Rotem Dror
Download or read book Statistical Significance Testing for Natural Language Processing written by Rotem Dror and published by Springer Nature. This book was released on 2022-06-01 with total page 98 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-driven experimental analysis has become the main evaluation tool of Natural Language Processing (NLP) algorithms. In fact, in the last decade, it has become rare to see an NLP paper, particularly one that proposes a new algorithm, that does not include extensive experimental analysis, and the number of involved tasks, datasets, domains, and languages is constantly growing. This emphasis on empirical results highlights the role of statistical significance testing in NLP research: If we, as a community, rely on empirical evaluation to validate our hypotheses and reveal the correct language processing mechanisms, we better be sure that our results are not coincidental. The goal of this book is to discuss the main aspects of statistical significance testing in NLP. Our guiding assumption throughout the book is that the basic question NLP researchers and engineers deal with is whether or not one algorithm can be considered better than another one. This question drives the field forward as it allows the constant progress of developing better technology for language processing challenges. In practice, researchers and engineers would like to draw the right conclusion from a limited set of experiments, and this conclusion should hold for other experiments with datasets they do not have at their disposal or that they cannot perform due to limited time and resources. The book hence discusses the opportunities and challenges in using statistical significance testing in NLP, from the point of view of experimental comparison between two algorithms. We cover topics such as choosing an appropriate significance test for the major NLP tasks, dealing with the unique aspects of significance testing for non-convex deep neural networks, accounting for a large number of comparisons between two NLP algorithms in a statistically valid manner (multiple hypothesis testing), and, finally, the unique challenges yielded by the nature of the data and practices of the field.
Book Synopsis What If There Were No Significance Tests? by : Lisa L. Harlow
Download or read book What If There Were No Significance Tests? written by Lisa L. Harlow and published by Routledge. This book was released on 2016-03-02 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: The classic edition of What If There Were No Significance Tests? highlights current statistical inference practices. Four areas are featured as essential for making inferences: sound judgment, meaningful research questions, relevant design, and assessing fit in multiple ways. Other options (data visualization, replication or meta-analysis), other features (mediation, moderation, multiple levels or classes), and other approaches (Bayesian analysis, simulation, data mining, qualitative inquiry) are also suggested. The Classic Edition’s new Introduction demonstrates the ongoing relevance of the topic and the charge to move away from an exclusive focus on NHST, along with new methods to help make significance testing more accessible to a wider body of researchers to improve our ability to make more accurate statistical inferences. Part 1 presents an overview of significance testing issues. The next part discusses the debate in which significance testing should be rejected or retained. The third part outlines various methods that may supplement significance testing procedures. Part 4 discusses Bayesian approaches and methods and the use of confidence intervals versus significance tests. The book concludes with philosophy of science perspectives. Rather than providing definitive prescriptions, the chapters are largely suggestive of general issues, concerns, and application guidelines. The editors allow readers to choose the best way to conduct hypothesis testing in their respective fields. For anyone doing research in the social sciences, this book is bound to become "must" reading. Ideal for use as a supplement for graduate courses in statistics or quantitative analysis taught in psychology, education, business, nursing, medicine, and the social sciences, the book also benefits independent researchers in the behavioral and social sciences and those who teach statistics.
Book Synopsis Introductory Business Statistics by : Alexander Holmes
Download or read book Introductory Business Statistics written by Alexander Holmes and published by . This book was released on 2017-11-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences.
Book Synopsis Statistical Power Analysis for the Behavioral Sciences by : Jacob Cohen
Download or read book Statistical Power Analysis for the Behavioral Sciences written by Jacob Cohen and published by Routledge. This book was released on 2013-05-13 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistical Significance by : John MacInnes
Download or read book Statistical Significance written by John MacInnes and published by SAGE. This book was released on 2019-01-21 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: You can′t get anywhere in your statistics course without grasping statistical significance. it′s often seen as difficult but is actually a straightforward concept everyone can—and should—understand. Do your results mean something—or not? How can you measure it? Breaking it down into three building blocks, this Little Quick Fix shows students how to master: hypothesis testing normal distribution p values Students will learn how to understand the concept and also how to explain it for maximum effect in their essays and lab reports. Good for results—this is also a secret weapon for critical thinking. Little Quick Fix titles provide quick but authoritative answers to the problems, hurdles, and assessment points students face in the research course, project proposal, or design—whatever their methods learning is. Lively, ultra-modern design; full-colour, each page a tailored design. An hour′s read. Easy to dip in and out of with clear navigation enables the reader to find what she needs—quick. Direct written style gets to the point with clear language. Nothing needs to be read twice. No fluff. Learning is reinforced through a 2-minute overview summary; 3-second summaries with super-quick Q&A DIY tasks create a work plan to accomplish a task, do a self-check quiz, solve a problem, get students to what they need to show their supervisor. Checkpoints in each section make sure students are nailing it as they go and support self-directed learning. How do I know I’m done? Each Little Quick Fix wraps up with a final checklist that allows the reader to self-assess they’ve got what they need to progress, submit, or ace the test or task.
Book Synopsis Statistical Significance by : Siu L Chow
Download or read book Statistical Significance written by Siu L Chow and published by SAGE. This book was released on 1996 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and accessible book provides an overview of the central and most fundamental methodological issue for empirical researchers - how should we interpret statistical significance? Beginning with a thorough introduction to null-hypothesis testing and statistical significance, the book then advances the arguments for and against the current interpretations and the use of significance testing in research. Siu L Chow presents a coherent challenge to contemporary criticisms of significance testing and offers a substantial and thought-provoking contribution to the debate on the proper role of statistical significance in empirical research.
Download or read book Data Driven written by Thomas C. Redman and published by Harvard Business Press. This book was released on 2008-09-22 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
Book Synopsis Statistical Significance by : John MaccInes
Download or read book Statistical Significance written by John MaccInes and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Introductory Statistics for the Life and Biomedical Sciences by : Julie Vu
Download or read book Introductory Statistics for the Life and Biomedical Sciences written by Julie Vu and published by . This book was released on 2020-03 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Statistics for the Life and Biomedical Sciences has been written to be used in conjunction with a set of self-paced learning labs. These labs guide students through learning how to apply statistical ideas and concepts discussed in the text with the R computing language.The text discusses the important ideas used to support an interpretation (such as the notion of a confidence interval), rather than the process of generating such material from data (such as computing a confidence interval for a particular subset of individuals in a study). This allows students whose main focus is understanding statistical concepts to not be distracted by the details of a particular software package. In our experience, however, we have found that many students enter a research setting after only a single course in statistics. These students benefit from a practical introduction to data analysis that incorporates the use of a statistical computing language.In a classroom setting, we have found it beneficial for students to start working through the labs after having been exposed to the corresponding material in the text, either from self-reading or through an instructor presenting the main ideas. The labs are organized by chapter, and each lab corresponds to a particular section or set of sections in the text.There are traditional exercises at the end of each chapter that do not require the use of computing. In the current posting, Chapters 1 - 5 have end-of-chapter exercises. More complicated methods, such as multiple regression, do not lend themselves to hand calculation and computing is necessary for gaining practical experience with these methods. The lab exercises for these later chapters become an increasingly important part of mastering the material.An essential component of the learning labs are the "Lab Notes" accompanying each chapter. The lab notes are a detailed reference guide to the R functions that appear in the labs, written to be accessible to a first-time user of a computing language. They provide more explanation than available in the R help documentation, with examples specific to what is demonstrated in the labs.
Book Synopsis Beyond Significance Testing by : Rex B. Kline
Download or read book Beyond Significance Testing written by Rex B. Kline and published by Amer Psychological Assn. This book was released on 2013 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traditional education in statistics that emphasises significance testing leaves researchers and students ill prepared to understand what their results really mean. Specifically, most researchers and students who do not have strong quantitative backgrounds have difficulty understanding outcomes of statistical tests. As more and more people become aware of this problem, the emphasis on statistical significance in the reporting of results is declining. Increasingly, researchers are expected to describe the magnitudes and precisions of their findings and also their practical, theoretical, or clinical significance. This accessibly written book reviews the controversy about significance testing, which has now crossed various disciplines as diverse as psychology, ecology, commerce, education, and biology, among others. It also introduces readers to alternative methods, especially effect size estimation (at both the group and case levels) and interval estimation (confidence intervals) in comparative studies. Basics of bootstrapping and Bayesian estimation are also considered. Research examples from substance abuse, education, learning, and other areas illustrate how to apply these methods. A companion website promotes learning by providing chapter exercises and sample answers, downloadable raw data files for many research examples, and links to other useful websites. New to this edition is coverage of robust statistical methods for parameter estimation, effect size estimation, and interval estimation. A new chapter covers the logic and illogic of significance testing. This edition also addresses recent developments such as the new requirements of some journals for the reporting of effect sizes.
Book Synopsis The Cult of Statistical Significance by : Deirdre Nansen McCloskey
Download or read book The Cult of Statistical Significance written by Deirdre Nansen McCloskey and published by University of Michigan Press. This book was released on 2010-02-11 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: “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).
Book Synopsis HBR Guide to Dealing with Conflict (HBR Guide Series) by : Amy Gallo
Download or read book HBR Guide to Dealing with Conflict (HBR Guide Series) written by Amy Gallo and published by Harvard Business Review Press. This book was released on 2017-03-14 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: While some of us enjoy a lively debate with colleagues and others prefer to suppress our feelings over disagreements, we all struggle with conflict at work. Every day we navigate an office full of competing interests, clashing personalities, limited time and resources, and fragile egos. Sure, we share the same overarching goals as our colleagues, but we don't always agree on how to achieve them. We work differently. We rub each other the wrong way. We jockey for position. How can you deal with conflict at work in a way that is both professional and productive—where it improves both your work and your relationships? You start by understanding whether you generally seek or avoid conflict, identifying the most frequent reasons for disagreement, and knowing what approaches work for what scenarios. Then, if you decide to address a particular conflict, you use that information to plan and conduct a productive conversation. The HBR Guide to Dealing with Conflict will give you the advice you need to: Understand the most common sources of conflict Explore your options for addressing a disagreement Recognize whether you—and your counterpart—typically seek or avoid conflict Prepare for and engage in a difficult conversation Manage your and your counterpart's emotions Develop a resolution together Know when to walk away Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.
Book Synopsis Statistical Power Analysis by : Kevin R. Murphy
Download or read book Statistical Power Analysis written by Kevin R. Murphy and published by Routledge. This book was released on 2003-08-01 with total page 247 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a simple and general method for conducting statistical power analysis based on the widely used F statistic. The book illustrates how these analyses work and how they can be applied to problems of studying design, to evaluate others' research, and to choose the appropriate criterion for defining "statistically significant" outcomes. Statistical Power Analysis examines the four major applications of power analysis, concentrating on how to determine: *the sample size needed to achieve desired levels of power; *the level of power that is needed in a study; *the size of effect that can be reliably detected by a study; and *sensible criteria for statistical significance. Highlights of the second edition include: a CD with an easy-to-use statistical power analysis program; a new chapter on power analysis in multi-factor ANOVA, including repeated-measures designs; and a new One-Stop PV Table to serve as a quick reference guide. The book discusses the application of power analysis to both traditional null hypothesis tests and to minimum-effect testing. It demonstrates how the same basic model applies to both types of testing and explains how some relatively simple procedures allow researchers to ask a series of important questions about their research. Drawing from the behavioral and social sciences, the authors present the material in a nontechnical way so that readers with little expertise in statistical analysis can quickly obtain the values needed to carry out the power analysis. Ideal for students and researchers of statistical and research methodology in the social, behavioral, and health sciences who want to know how to apply methods of power analysis to their research.
Book Synopsis Statistics Done Wrong by : Alex Reinhart
Download or read book Statistics Done Wrong written by Alex Reinhart and published by No Starch Press. This book was released on 2015-03-01 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Statistics For Dummies by : Deborah J. Rumsey
Download or read book Statistics For Dummies written by Deborah J. Rumsey and published by John Wiley & Sons. This book was released on 2016-06-07 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fun and easy way to get down to business with statistics Stymied by statistics? No fear? this friendly guide offers clear, practical explanations of statistical ideas, techniques, formulas, and calculations, with lots of examples that show you how these concepts apply to your everyday life. Statistics For Dummies shows you how to interpret and critique graphs and charts, determine the odds with probability, guesstimate with confidence using confidence intervals, set up and carry out a hypothesis test, compute statistical formulas, and more. Tracks to a typical first semester statistics course Updated examples resonate with today's students Explanations mirror teaching methods and classroom protocol Packed with practical advice and real-world problems, Statistics For Dummies gives you everything you need to analyze and interpret data for improved classroom or on-the-job performance.
