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.

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.

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.

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

Download or read book Tests of Significance written by Ramon E. Henkel and published by SAGE. This book was released on 1976-09 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: An elementary introduction to significance testing, this paper provides a conceptual and logical basis for understanding these tests.

Download or read book The Basic Practice of Statistics written by David S. Moore and published by Palgrave Macmillan. This book was released on 2010 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a clear and innovative overview of statistics which emphasises major ideas, essential skills and real-life data. The organisation and design has been improved for the fifth edition, coverage of engaging, real-world topics has been increased and content has been updated to appeal to today's trends and research.

Download or read book Understanding Significance Testing written by Lawrence B. Mohr and published by SAGE. This book was released on 1990-02 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The book begins with a clear and readable explanation of the idea of the sampling distribution....This text should be useful to the nonstatistical social researcher who wants to understand the concept of significance testing." --Social Research Association News "Good for refreshing a few basic ideas." --Journal of the American Statistical Association Significance testing is the most used, and arguably the most useful, of all techniques for analyzing social science data. In this practical volume, Mohr first defines basic terms such as variance, standard deviation, and parameter. He then carefully outlines the uses of significance testing and examines sampling distributions, probability distributions, and normal and t-tests of significance. Readers at all levels of research experience, from the first-semester student to the seasoned practitioner, will profit from this handy volume.

Download or read book Introductory Business Statistics paperback B w written by Alexander Holmes and published by . This book was released on 2023-06-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Printed in b&w. 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.

Download or read book Advances in Knowledge Discovery and Data Mining written by Honghua Dai and published by Springer Science & Business Media. This book was released on 2004-05-11 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.

Download or read book The Significance Test Controversy written by Denton E. Morrison and published by Transaction Publishers. This book was released on 2006-10-30 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tests of significance have been a key tool in the research kit of behavioral scientists for nearly fifty years, but their widespread and uncritical use has recently led to a rising volume of controversy about their usefulness. This book gathers the central papers in this continuing debate, brings the issues into clear focus, points out practical problems and philosophical pitfalls involved in using the tests, and provides a benchmark from which further analysis can proceed. The papers deal with some of the basic philosophy of science, mathematical and statistical assumptions connected with significance tests and the problems of the interpretation of test results, but the work is essentially non-technical in its emphasis. The collection succeeds in raising a variety of questions about the value of the tests; taken together, the questions present a strong case for vital reform in test use, if not for their total abandonment in research. The book is designed for practicing researchers-those not extensively trained in mathematics and statistics that must nevertheless regularly decide if and how tests of significance are to be used-and for those training for research. While controversy has been centered in sociology and psychology, and the book will be especially useful to researchers and students in those fields, its importance is great across the spectrum of the scientific disciplines in which statistical procedures are essential-notably political science, economics, and the other social sciences, education, and many biological fields as well. Denton E. Morrison is professor, Department of Sociology, Michigan State University. Ramon E. Henkel is associate professor emeritus, Department of Sociology University of Maryland. He teaches as part of the graduate faculty.

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

Download or read book Understanding Significance Testing written by Lawrence B. Mohr and published by Sage Publications (CA). This book was released on 1990 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significance testing - a core technique in statistics for hypothesis testing - is introduced in this volume. Mohr first reviews what is meant by sampling and probability distributions and then examines in-depth normal and t-tests of significance. The uses and misuses of significance testing are also explored.

Download or read book Statistics for the Behavioral Sciences written by Gregory J. Privitera and published by SAGE. This book was released on 2011-09-07 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics for the Behavioral Sciences is an introduction to statistics text that will engage students in an ongoing spirit of discovery by illustrating how statistics apply to modern-day research problems. By integrating instructions, screenshots, and practical examples for using IBM SPSS® Statistics software, the book makes it easy for students to learn statistical concepts within each chapter. Gregory J. Privitera takes a user-friendly approach while balancing statistical theory, computation, and application with the technical instruction needed for students to succeed in the modern era of data collection, analysis, and statistical interpretation.

Download or read book Hypothesis Testing written by Scott Hartshorn and published by . This book was released on 2017-10-29 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hypothesis Testing & Statistical Significance If you are looking for a short beginners guide packed with visual examples, this booklet is for you. Statistical significance is a way of determining if an outcome occurred by random chance, or did something cause that outcome to be different than the expected baseline. Statistical significance calculations find their way into scientific and engineering tests of all kinds, from medical tests with control group and a testing group, to the analysis of how strong a newly made batch of parts is. Those same calculations are also used in investment decisions. This book goes through all the major types of statistical significance calculations, and works through an example using them, and explains when you would use that specific type instead of one of the others. Just as importantly, this book is loaded with visual examples of what exactly statistical significance is, and the book doesn't assume that you have prior in depth knowledge of statistics or that use regularly use an advanced statistics software package. If you know what an average is and can use Excel, this book will build the rest of the knowledge, and do so in an intuitive way. For instance did you know that Statistical Significance Can Be Easily Understood By Rolling A Few Dice? In fact, you probably already know this key concept in statistical significance, although you might not have made the connection. The concept is this. Roll a single die. Is any number more likely to come up than another ? No, they are all equally likely. Now roll 2 dice and take their sum. Suddenly the number 7 is the most likely sum (which is why casinos win on it in craps). The probability of the outcome of any single die didn't change, but the probability of the outcome of the average of all the dice rolled became more predictable. If you keep increasing the number of dice rolled, the outcome of the average gets more and more predictable. This is the exact same effect that is at the heart of all the statistical significance equations (and is explained in more detail in the book) You Are Looking At Revision 2 Of This Book The book that you are looking at on Amazon right now is the second revision of the book. Earlier I said that you might have missed the intuitive connections to statistical significance that you already knew. Well that is because I missed them in the first release of this book. The first release included examples for the major types of statistical significance A Z-Test A 1 Sample T-Test A Paired T Test A 2 Sample T-Test with equal variance A 2 Sample T-test with unequal variance Descriptions of how to use a T-table and a Z-table And those examples were good for what they were, but were frankly not significantly different than you could find in many statistics textbooks or on Wikipedia. However this revision builds on those examples, draws connections between them, and most importantly explains concepts such as the normal curve or statistical significance in a way that will stick with you even if you don't remember the exact equation. If you are a visual learner and like to learn by example, this intuitive booklet might be a good fit for you. Statistical Significance is fascinating topic and likely touches your life every single day. It is a very important tool that is used in data analysis throughout a wide-range of industries - so take an easy dive into the topic with this visual approach!

Download or read book Using and Interpreting Statistics in the Social Behavioral and Health Sciences written by William E. Wagner, III and published by SAGE Publications. This book was released on 2018-02-28 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using and Interpreting Statistics in the Social, Behavioral, and Health Sciences is designed to be paired with any undergraduate introduction to research methods text used by students in a variety of disciplines. It introduces students to statistics at the conceptual level—examining the meaning of statistics, and why researchers use a particular statistical technique, rather than computational skills. Focusing on descriptive statistics, and some more advanced topics such as tests of significance, measures of association, and regression analysis, this brief, inexpensive text is the perfect companion to help students who have not yet taken an introductory statistics course or are confused by the statistics used in the articles they are reading.

Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com

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.