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| define spurious relationship: Calling Bullshit Carl T. Bergstrom, Jevin D. West, 2021-04-20 Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism. |
| define spurious relationship: The Essentials of Political Analysis Philip H. Pollock III, Barry C. Edwards, 2019-08-06 Pollock and Edwards explain the nuts-and-bolts of research design and data analysis in a clear and concise style. The Essential of Political Analysis is an intuitive introduction to complex material, replete with examples from the political science literature that add relevance to statistical concepts. This text offers students an excellent balance between the technical and the practical. —Francis Neely, San Francisco State University Gain the skills you need to conduct political analysis and critically assess statistical research. In this Sixth Edition of The Essentials of Political Science, bestselling authors Philip H. Pollock III and Barry C. Edwards build students’ analytic abilities and develop their statistical reasoning with new data, fresh exercises, and accessible examples. This brief, accessible guide walks students through the essentials—measuring concepts, formulating and testing hypotheses, describing variables—while using key terms, chapter-opening objectives, over 80 tables and figures, and practical exercises to get them using and applying their new skills. Using SPSS, STATA or R? Discounted package deals available with Philip H. Pollock’s companion workbooks. . Give your students the SAGE edge! SAGE edge offers a robust online environment featuring an impressive array of free tools and resources for review, study, and further exploration, keeping both instructors and students on the cutting edge of teaching and learning. |
| define spurious relationship: Introduction to Data Science Rafael A. Irizarry, 2019-11-12 Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. A complete solutions manual is available to registered instructors who require the text for a course. |
| define spurious relationship: Introduction to Family Processes Randal D. Day, 2014-09-04 What goes on behind closed doors in families is examined in this text. Through his storytelling style, Randy Day introduces readers to the family processes approach – the strategies and behaviors families use to achieve goals. The emphasis is on how families work and interact rather than on the psychological, sociological, or economic processes. It examines emotions in families, communication, relationship formation/dissolution, family rituals, and power and conflict. Chapters open with a Preview and conclude with a Summary, Study Questions, Key Terms, and Suggested Readings. Principle Boxes highlight key concepts and a Glossary defines the key terms listed at the ends of the chapters. Significantly updated with 50% new material including many new references and examples, the new edition features: A new chapter that introduces the discipline’s methodology A new chapter on relationship formation including partner selection, falling in love, commitment, sexuality, passion, and intimacy A new design reformatted to tie in with the book’s website at http://www.psypress.com/family-processes which now contains the Chapter Activity Questions that reinforce critical thinking skills, the Journal Activities that strengthen students' personal connection to the material, and the chapter Previews and Key Terms for review purposes An Instructor’s Web Resource at http://www.psypress.com/family-processes with small group and in-class exercises, lecture outlines in PowerPoint, topics for debate, suggested films, and multiple-choice, true/false, matching, and essay questions More material on the role of gender, power, genetics, and personality in relationships; families from diverse cultural and ethnic backgrounds and the impact of work and technology on the family; the changing nature of family structures including single parenting and gay unions; and stresses in family life. Written for undergraduate courses on family processes, family dynamics, family life, the family, and/or marriage & family interaction taught in family studies, human development, psychology, sociology, social work, education, consumer sciences, home economics, health, and nursing departments, this book also appeals to those who want to maximize the positive parts of family life and manage the inevitable challenges. |
| define spurious relationship: Picturing Hegel Julie E. Maybee, 2009-01-01 In her innovative take on G.W. F. Hegel's The Encyclopaedia Logic, Julie E. Maybee uses pictures and diagrams to cut through the philosopher's dense, difficult writing. Picturing Hegel: An Illustrated Guide to Hegel's Encyclopaedia Logic utilizes diagrams in order to rehabilitate Hegel's logic for serious consideration by showing how each stage develops step-by-step from earlier stages according to definite, logical patterns. This interpretation makes Hegel's work accessible and understandable for new and experienced readers alike. Because Hegel uses the same logic in all of his works, Maybee's analysis and defense of the logic will capture the attention of those readers interested in Hegel's ethics, politics, history, philosophy of religion, and phenomenology. Through the included diagrams, Maybee is able to define central Hegelian concepts such as 'being-in-itself, ' and 'being-in-and-for-itself' with a new level of precision. Maybee argues that Hegel's logic does not include the one logistical pattern most often attributed to him; namely, the pattern 'thesis-antithesis-synthesis.' Rather, Hegel's model of logic was more scientific than formalistic in nature, as the philosopher himself pointed out. Hegel considered himself an encyclopedic culmination of Western philosophy in some ways, and indeed his work summarizes many of the presuppositions of Western philosophy. By picturing Hegel's logic, we can gain a greater understanding of ourselves. |
| define spurious relationship: Naked Statistics: Stripping the Dread from the Data Charles Wheelan, 2013-01-07 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. |
| define spurious relationship: Theory-Based Data Analysis for the Social Sciences Carol S. Aneshensel, 2013 This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of third variables to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions. |
| define spurious relationship: Information Systems Research Methods, Epistemology, and Applications Cater-Steel, Aileen, Al-Hakim, Latif, 2008-11-30 The book deals with the concepts and applications of information systems research, both theoretical concepts of information systems research and applications--Provided by publisher. |
| define spurious relationship: Practical Statistics for Data Scientists Peter Bruce, Andrew Bruce, 2017-05-10 Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data |
| define spurious relationship: Introductory Business Statistics 2e Alexander Holmes, Barbara Illowsky, Susan Dean, 2023-12-13 Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License. |
| define spurious relationship: Using Stata for Quantitative Analysis Kyle C. Longest, 2014-07-02 Using Stata for Quantitative Analysis, Second Edition offers a brief, but thorough introduction to analyzing data with Stata software. It can be used as a reference for any statistics or methods course across the social, behavioral, and health sciences since these fields share a relatively similar approach to quantitative analysis. In this book, author Kyle Longest teaches the language of Stata from an intuitive perspective, furthering students’ overall retention and allowing a student with no experience in statistical software to work with data in a very short amount of time. The self-teaching style of this book enables novice Stata users to complete a basic quantitative research project from start to finish. The Second Edition covers the use of Stata 13 and can be used on its own or as a supplement to a research methods or statistics textbook. |
| define spurious relationship: Researching Translation Competence by PACTE Group Amparo Hurtado Albir, 2017-02-15 This volume is a compendium of PACTE Group’s experimental research in Translation Competence since 1997. The book is organised in four main parts and also includes eight appendices and a glossary. Part I presents the conceptual and methodological framework of PACTE’s Translation Competence research design. Part II focuses on the methodological aspects of the research design and its development: exploratory tests and pilot studies carried out; experiment design; characteristics of the sample population; procedures of data collection and analysis. Part III presents the results obtained in the experiment related to: the Acceptability of the translations produced in the experiment and the six dependent variables of study (Knowledge of Translation; Translation Project; Identification and Solution of Translation Problems; Decision-making; Efficacy of the Translation Process; Use of Instrumental Resources); this part also includes a corpus analysis of the translations. Part IV analyses the translators who were ranked highest in the experiment and goes on to present final conclusions as well as PACTE’s perspectives in the field of Translation Competence research. |
| define spurious relationship: Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide Agency for Health Care Research and Quality (U.S.), 2013-02-21 This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov) |
| define spurious relationship: Unhealthy Societies Richard G. Wilkinson, 2002-09-11 Book and author to be featured on Channel 4 Equinox series Author is well-known in his field internationally Breaks new ground by explaining the relationship between equality and health Argues that the amount of income equality in a society is a powerful determinant of its average life expectancy - controversial PUBLICITY TITLE |
| define spurious relationship: Quantitative Investment Analysis Workbook Richard A. DeFusco, Dennis W. McLeavey, Jerald E. Pinto, David E. Runkle, 2010-12-22 In Quantitative Investment Analysis Workbook, Second Edition, financial experts Richard DeFusco, Dennis McLeavey, Jerald Pinto, and David Runkle offer you a wealth of practical information and exercises that will further enhance your understanding of this discipline. This essential study guide—which parallels the main book chapter by chapter—contains challenging problems and a complete set of solutions as well as concise learning outcome statements and summary overviews. |
| define spurious relationship: Methodology of Sociological Research S. Nowak, 2012-12-06 This is the first part of a textbook for students of sociology, and for those students of other social sciences who wish to make use in their work of the research methods elaborated in the course of the develop ment of empirical sociology over the last few decades. The development of empirical sociological research in our country and the growing demand both for a practical application of its results and for graduates of sociological studies in various fields of social practice testifies to a much broader trend. It is evidence of a desire to base our understanding and conscious transformation of social phenom ena on a sound, scientific perception of social processes and the mechanisms governing them. The increasing volume of studies in Poland is accompanied by a growing need for a particular type of re search method, namely one in which questions addressed to the socio logist would be answered in a manner as free as possible of conclusions based on impressions and defining as unambiguously as possible both the limits of the generality and the degree of validity of the inferences drawn from the results of the research. These conditions are met by the so-called standardized methods of investigating social phenomena which, together with statistical methods of analyzing collected material, consti tute the principal means of conducting sociological research in the world today. |
| define spurious relationship: The SAGE Encyclopedia of Communication Research Methods Mike Allen, 2017-04-11 Communication research is evolving and changing in a world of online journals, open-access, and new ways of obtaining data and conducting experiments via the Internet. Although there are generic encyclopedias describing basic social science research methodologies in general, until now there has been no comprehensive A-to-Z reference work exploring methods specific to communication and media studies. Our entries, authored by key figures in the field, focus on special considerations when applied specifically to communication research, accompanied by engaging examples from the literature of communication, journalism, and media studies. Entries cover every step of the research process, from the creative development of research topics and questions to literature reviews, selection of best methods (whether quantitative, qualitative, or mixed) for analyzing research results and publishing research findings, whether in traditional media or via new media outlets. In addition to expected entries covering the basics of theories and methods traditionally used in communication research, other entries discuss important trends influencing the future of that research, including contemporary practical issues students will face in communication professions, the influences of globalization on research, use of new recording technologies in fieldwork, and the challenges and opportunities related to studying online multi-media environments. Email, texting, cellphone video, and blogging are shown not only as topics of research but also as means of collecting and analyzing data. Still other entries delve into considerations of accountability, copyright, confidentiality, data ownership and security, privacy, and other aspects of conducting an ethical research program. Features: 652 signed entries are contained in an authoritative work spanning four volumes available in choice of electronic or print formats. Although organized A-to-Z, front matter includes a Reader’s Guide grouping entries thematically to help students interested in a specific aspect of communication research to more easily locate directly related entries. Back matter includes a Chronology of the development of the field of communication research; a Resource Guide to classic books, journals, and associations; a Glossary introducing the terminology of the field; and a detailed Index. Entries conclude with References/Further Readings and Cross-References to related entries to guide students further in their research journeys. The Index, Reader’s Guide themes, and Cross-References combine to provide robust search-and-browse in the e-version. |
| define spurious relationship: Abstracts of the Papers Printed in the Philosophical Transactions of the Royal Society of London Royal Society (Great Britain), 1897 |
| define spurious relationship: Dictionary of Nursing Theory and Research Bethel Ann Powers, RN, PhD, Thomas R. Knapp, EdD, 2010-12-10 Designated a Doody's Core Title! Praise for the previous edition: This reference is valuable to scholars at all levels of nursing and is especially useful to researchers. . . . With this volume at hand consumers of research and theory will learn more easily and quickly. Molly (Mickey) Dougherty, PhD, RN Professor of Nursing, University of North Carolina Editor, Nursing Research What distinguishes this Dictionary from others are its attention to the diversity in inquiry and distinctively nursing 'takes' on key concepts in theory and research. This Dictionary will be a welcome addition to the libraries of both new and experienced researchers. Margarete Sandelowski Cary C. Boshamer Distinguished Professor University of North Carolina at Chapel Hill The fourth edition of this classic dictionary for understanding traditional and new concepts in nursing theory and research encompasses the considerable changes that have occurred in the clinical health sciences since the previous edition was published. It includes updates and new references for entries from the previous edition, and information related to developing areas of research and practice. New content that reflects nursing priorities in research and theory development in the current interprofessional health care environment is featured. This book remains an invaluable reference for nursing students, researchers, theoreticians, and scholars. Key features: Includes new and updated entries on developing national and international research trends, such as translational research, implementation science, and comparative effectiveness research Contains content related to high-priority research areas, such as biological and biobehavioral research, outcomes research, health services research, and participatory models of research Presents cross-references and citations from relevant multinational nursing and interdisciplinary literature sources Incorporates information based on the scrutiny of students and faculty to ensure utmost clarity |
| define spurious relationship: Introduction to Educational Research W. Newton Suter, 2012 W. Newton Suter argues that what is important in a changing education landscape is the ability to think clearly about research methods, reason through complex problems and evaluate published research. He explains how to evaluate data and establish its relevance. |
| define spurious relationship: Statistics for Criminal Justice and Criminology in Practice and Research Jack Fitzgerald, Jerry Fitzgerald, 2013-01-17 Statistics in Criminal Justice and Criminology Research: An Introduction is for advanced undergraduate and graduate level students in criminology and criminal justice statistics courses. It is designed for students pursuing careers in criminology and/or criminal justice by adequately and evenly covering statistical research for both professions. The engaging writing style, real-life applications, and comprehensive format will distinguish this text from its competitors and help establish it as more than just another statistics book. Fitzgerald and Fitzgerald have teamed up to create a flexible and useful text that will not only meet the needs of criminal justiceiminology students but also provide motivation for students who have math anxiety yet strive to become criminal justice professionals.Features and Benefits:1) Frequent use of diagrams and graphs to illustrate ideas and procedures discussed in the text.2) Attention devoted to discussing 'conceptual' formulas and what they represent about the data to help students make sense of the results.3) Extensive sets of review questions and exercises at ends of chapters help students master the content presented. 4) Quotes from actual reports in 'From the Literature' boxes help connect the discussion of research methods and statistical analysis with the research process as a whole.5) 'Pause, Think and Explore' boxes follow the mathematical formulas and are intended to help students develop an understanding of how the formula works, gain confidence in working with the mathematics, and develop better insight about what the formulas are signaling about the data being analyzed. |
| define spurious relationship: A Guide to Basic Econometric Techniques Elia Kacapyr, 2015-03-04 This economical text is intended for use as a universal supplement to introductory econometrics courses. This edition contains two new chapters on economic forecasting. Extensive online supplements include teaching PowerPoints, solutions to test questions/problems, new instructor questions, and software programs with data to download. |
| define spurious relationship: Statistics for Criminal Justice and Criminology in Practice and Research Jack Fitzgerald, Jerry Fitzgerald, 2013-01-17 Statistics for Criminal Justice and Criminology in Practice and Research—by Jack Fitzgerald and Jerry Fitzgerald—is an engaging and comprehensive introduction to the study of basic statistics for students pursuing careers as practitioners or researchers in both Criminal Justice and Criminology programs. This student-friendly text shows how to calculate a variety of descriptive and inferential statistics, recognize which statistics are appropriate for particular data analysis situations, and perform hypothesis tests using inferential statistics. But it is much more than a cook book. It encourages readers to think critically about the strengths and limitations of the statistics they are calculating, as well as how they may be misapplied and misleading. Examples of statistics and statistical analyses are drawn from the worlds of the practitioner as well as the policymaker and researcher. Students will also gain a clear understanding of major ethical issues in conducting statistical analyses and reporting results, as well as insight into the realities of the life of researchers and practitioners as they use statistics and statistical analyses in their day-to-day activities. |
| define spurious relationship: The SAGE Dictionary of Statistics Duncan Cramer, Dennis Laurence Howitt, 2004-05-18 `The authors make excellent use of illustrative examples′ - Reference Reviews The SAGE Dictionary of Statistics provides students and researchers with an accessible and definitive resource to use when studying statistics in the social sciences, reading research reports and undertaking data analysis. Written by leading academics in the field of methodology and statistics, the Dictionary will be an essential study guide for the first-time researcher as well as a primary resource for more advanced study. This is a practical and concise dictionary that serves the everyday uses of statistics across the whole range of social science disciplines. It offers basic and straightforward definitions of key concepts, followed by more detailed step-by-step explanations of situating specific methods and techniques. It also contains lists of related concepts to help the user to draw connections across various fields and increase their overall understand of a specific technique. A list of key readings helps to reinforce the aim of the Dictionary as an invaluable learning resource. Designed specifically for students and those new to research, and written in a lively and engaging manner, this Dictionary is an essential reference work for students and researchers across the social sciences. |
| define spurious relationship: Statistical Rethinking Richard McElreath, 2016-01-05 Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas. |
| define spurious relationship: How To Cheat With Statistics - And Get Away With It: From Data Snooping Over Kitchen Sink Regression To "Creative Reporting" Gunter Meissner, 2022-09-02 The book explains how to identify and catch statistical cheaters. The author came across many weaknesses and flaws in statistics through 30 years of teaching. These weaknesses allow a malevolent researcher to manipulate the inputs, the calculations, and the reporting of results to derive a desired outcome.This book should be valuable to everyone who wants to gain a deeper understanding of the weaknesses in statistics and learn how to evaluate statistical research to catch a statistical cheater!The math is explained in simple terms and should be easy to follow. In addition, the book comes with 18 Excel spreadsheets and 7 Python codes. There are also questions and problems at the end of each chapter, which should facilitate the usage in a classroom. Answers to the questions and problems are available to instructors upon request. |
| define spurious relationship: DYNAMIC ECONOMETRIC STRUCTURAL STABILITY, COINTEGRATION AND PANEL DATA CESAR PEREZ LOPEZ, This book covers a wide typology of dynamic models including models with distributed delays, models with stochastic regressors, models with structural change and dynamic panel data models. Widely is the theory of unit roots, the Cointegration and error correction models. And all this from a perspective multi-software, using the latest software on the market suitable for these non-trivial econometric tasks (SAS, EVIEWS, SPSS and STATA). |
| define spurious relationship: Complex Networks and Their Applications XI Hocine Cherifi, Rosario Nunzio Mantegna, Luis M. Rocha, Chantal Cherifi, Salvatore Miccichè, 2023-01-03 This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the XI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2022). The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks and technological networks. |
| define spurious relationship: Econometrics: Alchemy or Science? David F. Hendry, 2000-10-26 Econometrics: Alchemy or Science? analyses the effectiveness and validity of applying econometric methods to economic time series. The methodological dispute is long-standing, and no claim can be made for a single valid method, but recent results on the theory and practice of model selection bid fair to resolve many of the contentious issues. The book presents criticisms and evaluations of competing approaches, based on theoretical economic and econometric analyses, empirical applications, and Monte Carlo simulations, which interact to determine best practice. It explains the evolution of an approach to econometric modelling founded in careful statistical analyses of the available data, using economic theory to guide the general model specification. From a strong foundation in the theory of reduction, via a range of applied and simulation studies, it demonstrates that general-to-specific procedures have excellent properties. The book is divided into four Parts: Routes and Route Maps; Empirical Modelling Strategies; Formalization; and Retrospect and Prospect. A short preamble to each chapter sketches the salient themes, links to earlier and later developments, and the lessons learnt or missed at the time. A sequence of detailed empirical studies of consumers' expenditure and money demand illustrate most facets of the approach. Material new to this revised edition describes recent major advances in computer-automated model selection, embodied in the powerful new software program PcGets, which establish the operational success of the modelling strategy. |
| define spurious relationship: Text Book of Correlations and Regression A.K. Sharma, 2005 This book Correlation and Regression is an outcome of authors long teaching experience of the subject. This book present a thorough treatment of what is required for the students of B.A/B.Sc., of all Indian Universities. It includes fundamental concepts, illustrated examples and application to various problems. These illustrative examples have been selected carefully on such topic and sufficient number of unsolved questions are provided which aims at sharpening the skill of students. Contents: Correlation Analysis, Regression Analysis, Partial and Multiple Correlation. |
| define spurious relationship: Causality Judea Pearl, 2009-09-14 Causality offers the first comprehensive coverage of causal analysis in many sciences, including recent advances using graphical methods. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artificial intelligence ... |
| define spurious relationship: Handbook of Data Analysis Melissa A Hardy, Alan Bryman, 2004-05-25 This text provides a reliable guide to the basic issues in data analysis, such as the construction of variables, the characterization of distributions and the notions of inference. |
| define spurious relationship: Handbook of Conflict Analysis and Resolution Dennis J.D. Sandole, Sean Byrne, Ingrid Sandole-Staroste, Jessica Senehi, 2008-07-31 This major Handbook comprises cutting-edge essays from leading scholars in the field of Conflict Analysis and Resolution (CAR). The volume provides a comprehensive overview of the core concepts, theories, approaches, processes, and intervention designs in the field. The central theme is the value of multidisciplinary approaches to the analysis and |
| define spurious relationship: Bias and Causation Herbert I. Weisberg, 2011-01-06 A one-of-a-kind resource on identifying and dealing with bias in statistical research on causal effects Do cell phones cause cancer? Can a new curriculum increase student achievement? Determining what the real causes of such problems are, and how powerful their effects may be, are central issues in research across various fields of study. Some researchers are highly skeptical of drawing causal conclusions except in tightly controlled randomized experiments, while others discount the threats posed by different sources of bias, even in less rigorous observational studies. Bias and Causation presents a complete treatment of the subject, organizing and clarifying the diverse types of biases into a conceptual framework. The book treats various sources of bias in comparative studies—both randomized and observational—and offers guidance on how they should be addressed by researchers. Utilizing a relatively simple mathematical approach, the author develops a theory of bias that outlines the essential nature of the problem and identifies the various sources of bias that are encountered in modern research. The book begins with an introduction to the study of causal inference and the related concepts and terminology. Next, an overview is provided of the methodological issues at the core of the difficulties posed by bias. Subsequent chapters explain the concepts of selection bias, confounding, intermediate causal factors, and information bias along with the distortion of a causal effect that can result when the exposure and/or the outcome is measured with error. The book concludes with a new classification of twenty general sources of bias and practical advice on how mathematical modeling and expert judgment can be combined to achieve the most credible causal conclusions. Throughout the book, examples from the fields of medicine, public policy, and education are incorporated into the presentation of various topics. In addition, six detailed case studies illustrate concrete examples of the significance of biases in everyday research. Requiring only a basic understanding of statistics and probability theory, Bias and Causation is an excellent supplement for courses on research methods and applied statistics at the upper-undergraduate and graduate level. It is also a valuable reference for practicing researchers and methodologists in various fields of study who work with statistical data. This book was selected as the 2011 Ziegel Prize Winner in Technometrics for the best book reviewed by the journal. It is also the winner of the 2010 PROSE Award for Mathematics from The American Publishers Awards for Professional and Scholarly Excellence |
| define spurious relationship: Time Series Modelling of Water Resources and Environmental Systems K.W. Hipel, A.I McLeod, 1994-04-07 This is a comprehensive presentation of the theory and practice of time series modelling of environmental systems. A variety of time series models are explained and illustrated, including ARMA (autoregressive-moving average), nonstationary, long memory, three families of seasonal, multiple input-single output, intervention and multivariate ARMA models. Other topics in environmetrics covered in this book include time series analysis in decision making, estimating missing observations, simulation, the Hurst phenomenon, forecasting experiments and causality. Professionals working in fields overlapping with environmetrics - such as water resources engineers, environmental scientists, hydrologists, geophysicists, geographers, earth scientists and planners - will find this book a valuable resource. Equally, environmetrics, systems scientists, economists, mechanical engineers, chemical engineers, and management scientists will find the time series methods presented in this book useful. |
| define spurious relationship: The Philosophy of Quantitative Methods Brian D. Haig, 2018-01-04 The Philosophy of Quantitative Methods focuses on the conceptual foundations of research methods within the behavioral sciences. In particular, it undertakes a close philosophical examination of a variety of quantitative research methods that are prominent in (or relevant for) the conduct of research in these fields. By doing so, the deep structure of these methods is examined in order to overcome the non-critical approaches typically found in the existing literature today. In this book, Brian D. Haig focuses on the more well-known research methods such as exploratory data analysis, statistical significant testing, Bayesian confirmation theory and statistics, meta-analysis, and exploratory factor analysis. These methods are then examined with a philosophy consistent of scientific realism. In addition, each chapter provides a helpful Further Reading section in order to better assist the reader in extending their own thinking and research methods specific to their needs. |
| define spurious relationship: Sociology David M. Newman, 2018-07-26 This new Brief Sixth Edition of David Newman’s text is the streamlined version of Sociology: Exploring the Architecture of Everyday Life with the same goal: to be a textbook that, in the author’s words, reads like a real book. Newman shows to see the “unfamiliar in the familiar”—to step back and see organization and predictability in their take-for-granted personal experiences. Newman uses the metaphors of “architecture” and “construction,” to help students understand that society is not something that exists “out there,” independently of themselves; it is a human creation that is planned, maintained, or altered by individuals. Instead of surveying every subfield in sociology, this text focuses on the structural features of society, the social construction of self and identity, and social inequality in the context of social institutions. The new edition includes examples and analysis of contemporary events and trends, including: The changes in our national politics brought about by the 2016 presidential election Increasing societal attention paid to fatal encounters between police and unarmed people of color or incidents of sexual harassment and assault School shootings and the debates over gun ownership The continued dramatic growth of communication technology, particularly social networking sites |
| define spurious relationship: The SAGE Handbook of Comparative Politics Todd Landman, Neil Robinson, 2009-06-30 ′Editors Landman and Robinson have compiled an excellent tour d′horizon of comparative politics. Distinguished contributors explore theoretical and methodological issues as well as examine the critical substantive domains that animate today′s comparativists. Graduate students and academics will want to keep this volume on their book shelf′ - Professor Mark Irving Lichbach, University of Maryland ′The SAGE Handbook of Comparative Politics is a major new resource for scholars of comparative politics, and of political science more generally. The Handbook covers the field with admirable thoroughness, but does not sacrifice depth for breadth. The chapters are written by notable scholars who provide rich discussions of their topics, and help to move the sub-discipline forward′ - B. Guy Peters, Professor, University of Pittsburgh The SAGE Handbook of Comparative Politics presents; in one volume, an authoritative overview of the theoretical, methodological and substantive elements of comparative political science. The 28 specially commissioned chapters, written by renowned comparative scholars, guide the reader through the central issues and debates, presenting a state-of-the-art guide to the past, present and possible futures of the field. The Handbook is divided into three parts. The first considers comparative methodologies and reviews the interactions between various sub-fields of comparative politics: political economy; political sociology; area studies; international relations; and institutional analysis. The second section examines nine ′classic′ issues of concern to comparativists, including government formation, political behaviour and democratization. In the final section, nine new and emerging areas of comparative research are considered, such as terrorism, electoral corruption, human rights and regional integration. The SAGE Handbook of Comparative Politics is an essential resource for researchers in political science, political sociology, political economy, international relations, area studies and all other fields with a comparative political dimension. |
| define spurious relationship: Research Methods in Practice Dahlia K. Remler, Gregg G. Van Ryzin, 2021-08-24 Thoroughly updated to reflect changes in both research and methods, this Third Edition of Remler and Van Ryzin’s innovative, standard-setting text is imbued with a deep commitment to making social and policy research methods accessible and meaningful. Research Methods in Practice: Strategies for Description and Causation motivates readers to examine the logic and limits of social science research from academic journals and government reports. A central theme of causation versus description runs through the text, emphasizing the idea that causal research is essential to understanding the origins of social problems and their potential solutions. Readers will find excitement in the research experience as the best hope for improving the world in which we live, while also acknowledging the trade-offs and uncertainties in real-world research. |
| define spurious relationship: New Voices in Higher Education Research and Scholarship Ribeiro, Filipa M., Politis, Yurgos, Culum, Bojana, 2014-11-30 Higher Education systems and universities worldwide are constantly being transformed due to ever-changing practices and policies. Recent research reveals the challenges between society and higher education continue to grow. New Voices in Higher Education Research and Scholarship explores the role of higher education in today’s society. It discusses the rapidly changing nature of higher education around the globe, especially the relationship between higher education and social development. This reference book will be of use to policymakers, academicians, researchers, students, and government officials. |
Spurious relationship - Wikipedia
The term "spurious relationship" is commonly used in statistics and in particular in experimental research techniques, both of which attempt to understand and predict direct causal …
5 Examples of Spurious Correlation in Real Life - Statology
Apr 25, 2022 · In statistics, spurious correlation refers to a correlation between two variables that occurs purely by chance without one variable actually causing the other to occur. This type of …
What is Spurious Correlation in Statistics (With Examples)
May 3, 2024 · A spurious correlation in statistics occurs when two variables have a direct relationship, but a third variable influences both. The apparent relationship between the two …
Spurious correlations: 15 examples - DataScienceCentral.com
Jan 26, 2016 · Besides, the standard correlation (an L^2 metric) is sensitive to outliers, and indeed, not a great metric. This L^1 metric (to measure correlation) is more robust. Below are …
Spurious Correlation: Definition, Examples & Detecting
What is a Spurious Correlation? A spurious correlation occurs when two variables are correlated but don’t have a causal relationship. In other words, it appears like values of one variable …
What Is a Spurious Correlation? (Definition and Examples)
Mar 17, 2025 · A spurious correlation is a mathematical relationship between two variables that statistically relate to each other, but don't relate casually without a common variable. In …
Spurious relationships - (Intro to Comparative Politics) - Fiveable
Spurious relationships refer to situations in research where two variables appear to be related but are actually both influenced by a third variable, leading to a false or misleading association. …
Spurious Correlation: Examples from Real Life and the News
What is a Spurious Correlation? A spurious correlation wrongly implies a cause and effect between two variables. For example, the number of astronauts dying in spacecraft is directly …
spurious correlation | Definition
What Is a Spurious Correlation? In social science research, a spurious correlation occurs when two variables appear to be related, but their connection is either accidental or driven by a third, …
Spurious Correlation: Definition, How It Works and Examples
Mar 4, 2025 · What is a spurious correlation? A spurious correlation is a situation where multiple variables relate to each other statistically, without a direct causal relationship. In statistics, the …
Spurious relationship - Wikipedia
The term "spurious relationship" is commonly used in statistics and in particular in experimental research techniques, both of which attempt to understand and predict direct causal …
5 Examples of Spurious Correlation in Real Life - Statology
Apr 25, 2022 · In statistics, spurious correlation refers to a correlation between two variables that occurs purely by chance without one variable actually causing the other to occur. This type of …
What is Spurious Correlation in Statistics (With Examples)
May 3, 2024 · A spurious correlation in statistics occurs when two variables have a direct relationship, but a third variable influences both. The apparent relationship between the two …
Spurious correlations: 15 examples - DataScienceCentral.com
Jan 26, 2016 · Besides, the standard correlation (an L^2 metric) is sensitive to outliers, and indeed, not a great metric. This L^1 metric (to measure correlation) is more robust. Below are …
Spurious Correlation: Definition, Examples & Detecting
What is a Spurious Correlation? A spurious correlation occurs when two variables are correlated but don’t have a causal relationship. In other words, it appears like values of one variable …
What Is a Spurious Correlation? (Definition and Examples)
Mar 17, 2025 · A spurious correlation is a mathematical relationship between two variables that statistically relate to each other, but don't relate casually without a common variable. In …
Spurious relationships - (Intro to Comparative Politics) - Fiveable
Spurious relationships refer to situations in research where two variables appear to be related but are actually both influenced by a third variable, leading to a false or misleading association. …
Spurious Correlation: Examples from Real Life and the News
What is a Spurious Correlation? A spurious correlation wrongly implies a cause and effect between two variables. For example, the number of astronauts dying in spacecraft is directly …
spurious correlation | Definition
What Is a Spurious Correlation? In social science research, a spurious correlation occurs when two variables appear to be related, but their connection is either accidental or driven by a third, …
Spurious Correlation: Definition, How It Works and Examples
Mar 4, 2025 · What is a spurious correlation? A spurious correlation is a situation where multiple variables relate to each other statistically, without a direct causal relationship. In statistics, the …
