Search Results for "understanding-psychology-as-a-science-an-introduction-to-scientific-and-statistical-inference"

Understanding Psychology as a Science

Understanding Psychology as a Science

An Introduction to Scientific and Statistical Inference

  • Author: Zoltan Dienes
  • Publisher: Macmillan International Higher Education
  • ISBN: 1137096055
  • Category: Psychology
  • Page: 184
  • View: 1110
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What makes psychology a science? What is the logic underlying psychological research? In this groundbreaking book Zoltán Dienes introduces students to key issues in the philosophy of science and statistics that have a direct and vital bearing on the practice of research in psychology. The book is organised around the influential thinkers and conceptual debates which pervade psychological research and teaching but until now have not been made accessible to students. In a clear and fluid style, Dienes takes the reader on a compelling tour of the ideas of: - Popper - Kuhn& Lakatos - Neyman& Pearson - Bayes - Fisher& Royall Featuring examples drawn from extensive teaching experience to ground the ideas firmly in psychological science, the book is an ideal companion to courses and modules in psychological research methods and also to those covering conceptual and historical issues.

Understanding Psychology as a Science

Understanding Psychology as a Science

An Introduction to Scientific and Statistical Inference

  • Author: Zoltan Dienes
  • Publisher: Red Globe Press
  • ISBN: 9780230542310
  • Category: Philosophy
  • Page: 184
  • View: 8311
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How can we objectively define categories of truth in scientific thinking? How can we reliably measure the results of research? In this ground-breaking text, Dienes undertakes a comprehensive historical analysis of the dominant schools of thought, key theories and influential thinkers that have progressed the foundational principles and characteristics that typify scientific research methodology today. This book delivers a masterfully simple, ‘though not simplistic’, introduction to the core arguments surrounding Popper, Kuhn and Lakatos, Fisher and Royall, Neyman and Pearson and Bayes. Subsequently, this book clarifies the prevalent misconceptions that surround such theoretical perspectives in psychology today, providing an especially accessible critique for student readers. This book launches an informative inquiry into the methods by which psychologists throughout history have arrived at the conclusions of research, equipping readers with the knowledge to accurately design and evaluate their own research and gain confidence in critiquing results in psychology research. Particular attention is given to understanding methods of measuring the falsifiability of statements, probabilities and the differing views on statistical inference. An illuminating book for any undergraduate psychology student taking courses in critical thinking, research methods, BPS’s core area ‘conceptual and historical issues’ as well as those studying masters, phd’s and experienced researchers.

Understanding Psychology as a Science

Understanding Psychology as a Science

An Introduction to Scientific and Statistical Inference

  • Author: Zoltán Dienes
  • Publisher: Palgrave Macmillan
  • ISBN: 9780230542310
  • Category: Philosophy
  • Page: 150
  • View: 9699
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An accessible and illuminating exploration of the conceptual basisof scientific and statistical inference and the practical impact this has on conducting psychological research. The book encourages a critical discussion of the different approaches and looks at some of the most important thinkers and their influence.

Introduction to Scientific Reasoning

Introduction to Scientific Reasoning

  • Author: Angela M. Potochnik,Cory Wright,Matteo Colombo
  • Publisher: Routledge
  • ISBN: 9781138920736
  • Category:
  • Page: 300
  • View: 6748
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There is widespread recognition at universities that a proper understanding of science is needed for all undergraduates. Good jobs are increasingly found in fields related to Science, Technology, Engineering, and Medicine (STEM), and science now enters almost all aspects of our daily lives. For these reasons, scientific literacy and an understanding of scientific methodology are now a foundational part of any undergraduate education (and not just the education of science majors). Recipes for Science provides an accessible introduction to the main concepts and methods of scientific reasoning. With the help of an array of contemporary and historical examples, definitions, visual aids, and exercises for active learning, the textbook helps to increase students¿ scientific literacy. The first part of the book covers the definitive features of science: naturalism, experimentation, modeling, and the merits and shortcomings of experimenting and modeling. The second part covers the main forms of inference in science: deductive, inductive, abductive, probabilistic, statistical, and causal. The book concludes with a discussion of explanation, theorizing and theory-change, and the relationship between science and society. The textbook is designed to be adaptable to a wide variety of different kinds of courses. In any of these different uses, the book helps students better navigate our scientific, 21st-century world, and it lays the foundation for more advanced undergraduate coursework in a wide variety of liberal arts and science courses. Key Features Helps students develop scientific literacy¿an essential aspect of any undergraduate education in the 21st century, including a broad understanding of scientific reasoning, methods, and concepts Is written for all beginning college students: preparing science majors for more focused work in a particular science; introducing the humanities¿ investigations of science; and helping non-science majors become more sophisticated consumers of scientific information Provides an abundance of both contemporary and historical examples Covers reasoning strategies and norms applicable in all fields of physical, life, and social sciences, as well as strategies and norms distinctive of specific sciences Includes visual aids to clarify and illustrate ideas Provides text boxes with related topics and helpful definitions of key terms, and includes a final Glossary with all key terms Includes Exercises for Active Learning at the end of each chapter, which will ensure full student engagement and mastery of the information include earlier in the chapter Provides annotated "For Further Reading" sections at the end of each chapter, guiding students to the best primary and secondary sources available Offers a continually developing Companion Website, with author-developed and crowdsourced materials, including:¿ syllabi for a variety of courses using this textbook bibliography of additional resources, including online materials sharable PowerPoint presentations and lecture notes ideas for additional exercises and¿extended projects

The Seven Deadly Sins of Psychology

The Seven Deadly Sins of Psychology

A Manifesto for Reforming the Culture of Scientific Practice

  • Author: Chris Chambers
  • Publisher: Princeton University Press
  • ISBN: 1400884942
  • Category: Psychology
  • Page: 288
  • View: 4290
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Why psychology is in peril as a scientific discipline—and how to save it Psychological science has made extraordinary discoveries about the human mind, but can we trust everything its practitioners are telling us? In recent years, it has become increasingly apparent that a lot of research in psychology is based on weak evidence, questionable practices, and sometimes even fraud. The Seven Deadly Sins of Psychology diagnoses the ills besetting the discipline today and proposes sensible, practical solutions to ensure that it remains a legitimate and reliable science in the years ahead. In this unflinchingly candid manifesto, Chris Chambers draws on his own experiences as a working scientist to reveal a dark side to psychology that few of us ever see. Using the seven deadly sins as a metaphor, he shows how practitioners are vulnerable to powerful biases that undercut the scientific method, how they routinely torture data until it produces outcomes that can be published in prestigious journals, and how studies are much less reliable than advertised. He reveals how a culture of secrecy denies the public and other researchers access to the results of psychology experiments, how fraudulent academics can operate with impunity, and how an obsession with bean counting creates perverse incentives for academics. Left unchecked, these problems threaten the very future of psychology as a science—but help is here. Outlining a core set of best practices that can be applied across the sciences, Chambers demonstrates how all these sins can be corrected by embracing open science, an emerging philosophy that seeks to make research and its outcomes as transparent as possible.

Evidence-Based Technical Analysis

Evidence-Based Technical Analysis

Applying the Scientific Method and Statistical Inference to Trading Signals

  • Author: David Aronson
  • Publisher: John Wiley & Sons
  • ISBN: 1118160584
  • Category: Business & Economics
  • Page: 544
  • View: 1235
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Evidence-Based Technical Analysis examines how you can apply the scientific method, and recently developed statistical tests, to determine the true effectiveness of technical trading signals. Throughout the book, expert David Aronson provides you with comprehensive coverage of this new methodology, which is specifically designed for evaluating the performance of rules/signals that are discovered by data mining.

Statistical Inference

Statistical Inference

  • Author: Michael W. Oakes
  • Publisher: Epidemiology Resources
  • ISBN: N.A
  • Category: Mathematics
  • Page: 185
  • View: 1135
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Measuring Identity

Measuring Identity

A Guide for Social Scientists

  • Author: Rawi Abdelal
  • Publisher: Cambridge University Press
  • ISBN: 0521518180
  • Category: Political Science
  • Page: 428
  • View: 1477
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Abdelal, Herrera, Johnston, and McDermott have brought together leading scholars from a variety of disciplines to consider the conceptual and methodological challenges associated with treating identity as a variable, offer a synthetic theoretical framework, and demonstrate the possibilities offered by various methods of measurement.

Positive Psychology

Positive Psychology

The Science of Happiness and Human Strengths

  • Author: Alan Carr
  • Publisher: Routledge
  • ISBN: 1136583084
  • Category: Psychology
  • Page: 432
  • View: 6381
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Remediating deficits and managing disabilities has been a central preoccupation for clinical psychologists. Positive Psychology, in contrast, is concerned with the enhancement of happiness and well-being, involving the scientific study of the role of personal strengths and positive social systems in the promotion of optimal wellbeing. Alan Carr's Positive Psychology has become essential reading for anyone requiring a thorough and accessible introduction to the field. This new edition retains all the features that made the first edition so popular, including: accounts of major theories and relevant research learning objectives chapter summaries research and personal development questions suggestions for further reading measures for use in research glossaries of new terms. The book has also been completely updated to take account of recent research and major advances, and includes a new chapter on Positive Psychotherapy, an extended account of research on character strengths and virtues, and a discussion of recent ground-breaking research on emotional intelligence. This new edition of Positive Psychology will prove a valuable resource for psychology students and lecturers, as well as those involved in postgraduate training in related areas such as clinical psychology, social work, counselling and psychotherapy.

The Foundations of Scientific Inference

The Foundations of Scientific Inference

50th Anniversary Edition

  • Author: Wesley C. Salmon
  • Publisher: University of Pittsburgh Press
  • ISBN: 0822982943
  • Category: Science
  • Page: 208
  • View: 1835
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After its publication in 1967, The Foundations of Scientific Inference taught a generation of students and researchers about the problem of induction, the interpretation of probability, and confirmation theory. Fifty years later, Wesley C. Salmon’s book remains one of the clearest introductions to these fundamental problems in the philosophy of science. With The Foundations of Scientific Inference, Salmon presented a coherent vision of the nature of scientific reasoning, explored the philosophical underpinnings of scientific investigation, and introduced readers to key movements in epistemology and to leading philosophers of the twentieth century—such as Karl Popper, Rudolf Carnap, and Hans Reichenbach—offering a critical assessment and developing his own distinctive views on topics that are still of central importance today. This anniversary edition of Salmon’s foundational work in the philosophy of science features a detailed introduction by Christopher Hitchcock, which examines the book’s origins, influences, and major themes, its impact and enduring effects, the disputes it raised, and its place in current studies, revisiting Salmon’s ideas for a new audience of philosophers, historians, scientists, and students.

Psychology Statistics For Dummies

Psychology Statistics For Dummies

  • Author: Donncha Hanna,Martin Dempster
  • Publisher: John Wiley & Sons
  • ISBN: 1119953944
  • Category: Psychology
  • Page: 464
  • View: 1803
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The introduction to statistics that psychology students can't afford to be without Understanding statistics is a requirement for obtaining and making the most of a degree in psychology, a fact of life that often takes first year psychology students by surprise. Filled with jargon-free explanations and real-life examples, Psychology Statistics For Dummies makes the often-confusing world of statistics a lot less baffling, and provides you with the step-by-step instructions necessary for carrying out data analysis. Psychology Statistics For Dummies: Serves as an easily accessible supplement to doorstop-sized psychology textbooks Provides psychology students with psychology-specific statistics instruction Includes clear explanations and instruction on performing statistical analysis Teaches students how to analyze their data with SPSS, the most widely used statistical packages among students

Introduction to Linear Models and Statistical Inference

Introduction to Linear Models and Statistical Inference

  • Author: Steven J. Janke,Frederick Tinsley
  • Publisher: John Wiley & Sons
  • ISBN: 0471740101
  • Category: Mathematics
  • Page: 576
  • View: 3555
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A multidisciplinary approach that emphasizes learning by analyzing real-world data sets This book is the result of the authors' hands-on classroom experience and is tailored to reflect how students best learn to analyze linear relationships. The text begins with the introduction of four simple examples of actual data sets. These examples are developed and analyzed throughout the text, and more complicated examples of data sets are introduced along the way. Taking a multidisciplinary approach, the book traces the conclusion of the analyses of data sets taken from geology, biology, economics, psychology, education, sociology, and environmental science. As students learn to analyze the data sets, they master increasingly sophisticated linear modeling techniques, including: * Simple linear models * Multivariate models * Model building * Analysis of variance (ANOVA) * Analysis of covariance (ANCOVA) * Logistic regression * Total least squares The basics of statistical analysis are developed and emphasized, particularly in testing the assumptions and drawing inferences from linear models. Exercises are included at the end of each chapter to test students' skills before moving on to more advanced techniques and models. These exercises are marked to indicate whether calculus, linear algebra, or computer skills are needed. Unlike other texts in the field, the mathematics underlying the models is carefully explained and accessible to students who may not have any background in calculus or linear algebra. Most chapters include an optional final section on linear algebra for students interested in developing a deeper understanding. The many data sets that appear in the text are available on the book's Web site. The MINITAB(r) software program is used to illustrate many of the examples. For students unfamiliar with MINITAB(r), an appendix introduces the key features needed to study linear models. With its multidisciplinary approach and use of real-world data sets that bring the subject alive, this is an excellent introduction to linear models for students in any of the natural or social sciences.

Statistical Inference as Severe Testing

Statistical Inference as Severe Testing

How to Get Beyond the Statistics Wars

  • Author: Deborah G. Mayo
  • Publisher: Cambridge University Press
  • ISBN: 1107054133
  • Category: Mathematics
  • Page: 474
  • View: 2622
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Unlock today's statistical controversies and irreproducible results by viewing statistics as probing and controlling errors.

Serious Stats

Serious Stats

A guide to advanced statistics for the behavioral sciences

  • Author: Thomas Baguley
  • Publisher: Macmillan International Higher Education
  • ISBN: 0230363555
  • Category: Psychology
  • Page: 864
  • View: 7055
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Ideal for experienced students and researchers in the social sciences who wish to refresh or extend their understanding of statistics, and to apply advanced statistical procedures using SPSS or R. Key theory is reviewed and illustrated with examples of how to apply these concepts using real data.

Causality

Causality

  • Author: Judea Pearl
  • Publisher: Cambridge University Press
  • ISBN: 1139643983
  • Category: Science
  • Page: N.A
  • View: 2624
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Written by one of the preeminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, economics, philosophy, cognitive science, and the health and social sciences. Judea Pearl presents and unifies the probabilistic, manipulative, counterfactual, and structural approaches to causation and devises simple mathematical tools for studying the relationships between causal connections and statistical associations. Cited in more than 2,100 scientific publications, it continues to liberate scientists from the traditional molds of statistical thinking. In this revised edition, Judea Pearl elucidates thorny issues, answers readers' questions, and offers a panoramic view of recent advances in this field of research. Causality will be of interest to students and professionals in a wide variety of fields. Dr Judea Pearl has received the 2011 Rumelhart Prize for his leading research in Artificial Intelligence (AI) and systems from The Cognitive Science Society.

Observation and Experiment

Observation and Experiment

An Introduction to Causal Inference

  • Author: Paul R. Rosenbaum
  • Publisher: Harvard University Press
  • ISBN: 067497557X
  • Category: Mathematics
  • Page: 400
  • View: 2496
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In the face of conflicting claims about some treatments, behaviors, and policies, the question arises: What is the most scientifically rigorous way to draw conclusions about cause and effect in the study of humans? In this introduction to causal inference, Paul Rosenbaum explains key concepts and methods through real-world examples.

An Elementary Introduction to Statistical Learning Theory

An Elementary Introduction to Statistical Learning Theory

  • Author: Sanjeev Kulkarni,Gilbert Harman
  • Publisher: John Wiley & Sons
  • ISBN: 9781118023464
  • Category: Mathematics
  • Page: 288
  • View: 6151
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A thought-provoking look at statistical learning theory and its role in understanding human learning and inductive reasoning A joint endeavor from leading researchers in the fields of philosophy and electrical engineering, An Elementary Introduction to Statistical Learning Theory is a comprehensive and accessible primer on the rapidly evolving fields of statistical pattern recognition and statistical learning theory. Explaining these areas at a level and in a way that is not often found in other books on the topic, the authors present the basic theory behind contemporary machine learning and uniquely utilize its foundations as a framework for philosophical thinking about inductive inference. Promoting the fundamental goal of statistical learning, knowing what is achievable and what is not, this book demonstrates the value of a systematic methodology when used along with the needed techniques for evaluating the performance of a learning system. First, an introduction to machine learning is presented that includes brief discussions of applications such as image recognition, speech recognition, medical diagnostics, and statistical arbitrage. To enhance accessibility, two chapters on relevant aspects of probability theory are provided. Subsequent chapters feature coverage of topics such as the pattern recognition problem, optimal Bayes decision rule, the nearest neighbor rule, kernel rules, neural networks, support vector machines, and boosting. Appendices throughout the book explore the relationship between the discussed material and related topics from mathematics, philosophy, psychology, and statistics, drawing insightful connections between problems in these areas and statistical learning theory. All chapters conclude with a summary section, a set of practice questions, and a reference sections that supplies historical notes and additional resources for further study. An Elementary Introduction to Statistical Learning Theory is an excellent book for courses on statistical learning theory, pattern recognition, and machine learning at the upper-undergraduate and graduate levels. It also serves as an introductory reference for researchers and practitioners in the fields of engineering, computer science, philosophy, and cognitive science that would like to further their knowledge of the topic.

Handbook of Research Methods in Social and Personality Psychology

Handbook of Research Methods in Social and Personality Psychology

  • Author: Harry T. Reis,Charles M. Judd
  • Publisher: Cambridge University Press
  • ISBN: 1139867369
  • Category: Psychology
  • Page: N.A
  • View: 9755
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This indispensable sourcebook covers conceptual and practical issues in research design in the field of social and personality psychology. Key experts address specific methods and areas of research, contributing to a comprehensive overview of contemporary practice. This updated and expanded second edition offers current commentary on social and personality psychology, reflecting the rapid development of this dynamic area of research over the past decade. With the help of this up-to-date text, both seasoned and beginning social psychologists will be able to explore the various tools and methods available to them in their research as they craft experiments and imagine new methodological possibilities.

An Introduction to Statistical Learning

An Introduction to Statistical Learning

with Applications in R

  • Author: Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
  • Publisher: Springer Science & Business Media
  • ISBN: 1461471389
  • Category: Mathematics
  • Page: 426
  • View: 2659
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Field Experiments and Their Critics

Field Experiments and Their Critics

Essays on the Uses and Abuses of Experimentation in the Social Sciences

  • Author: Dawn Langan Teele
  • Publisher: Yale University Press
  • ISBN: 0300199309
  • Category: Social Science
  • Page: 279
  • View: 9256
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In recent years, social scientists have engaged in a deep debate over the methods appropriate to their research. Their long reliance on passive observational collection of information has been challenged by proponents of experimental methods designed to precisely infer causal effects through active intervention in the social world. Some scholars claim that field experiments represent a new gold standard and the best way forward, while others insist that these methods carry inherent inconsistencies, limitations, or ethical dilemmas that observational approaches do not. This unique collection of essays by the most influential figures on every side of this debate reveals its most important stakes and will provide useful guidance to students and scholars in many disciplines.