Understanding and Using Statistics in Psychology takes the fear out of psychological statistics to help students understand why statistics are carried out, how to choose the best test, how to carry out the tests, and then perform the analysis in SPSS. Emphasizing the place of statistical analysis in the process of conducting research, from design to report writing, this accessible and straightforward guide takes a non-technical approach, encouraging the reader to understand why a particular test is being used and what the results mean in the context of a psychological study. The focus is on meaning and understanding rather than numerical calculation.
A Practical Introduction
Author: Jeremy Miles,Philip Banyard
This practical, conceptual introduction to statistical analysis by award-winning teacher Andrew N. Christopher uses published research with inherently interesting social sciences content to help students make clear connections between statistics and real life. Using a friendly, easy-to-understand presentation, Christopher walks students through the hand calculations of key statistical tools and provides step-by-step instructions on how to run the appropriate analyses for each type of statistic in SPSS and how to interpret the output. With the premise that a conceptual grasp of statistical techniques is critical for students to truly understand why they are doing what they are doing, the author avoids overly formulaic jargon and instead focuses on when and how to use statistical techniques appropriately.
Author: Andrew N. Christopher
Publisher: SAGE Publications
The spread of sophisticated computer packages and the machinery on which to run them has meant that procedures which were previously only available to experienced researchers with access to expensive machines and research students can now be carried out in a few seconds by almost every undergraduate. Understanding and Using Advanced Statistics provides the basis for gaining an understanding of what these analytic procedures do, when they should be used, and what the results provided signify. This comprehensive textbook guides students and researchers through the transition from simple statistics to more complex procedures with accessible language and illustration.
A Practical Guide for Students
Author: Jeremy J Foster,Emma Barkus,Christian Yavorsky
Requiring no prior training, Modern Statistics for the Social and Behavioral Sciences provides a two-semester, graduate-level introduction to basic statistical techniques that takes into account recent advances and insights that are typically ignored in an introductory course. Hundreds of journal articles make it clear that basic techniques, routinely taught and used, can perform poorly when dealing with skewed distributions, outliers, heteroscedasticity (unequal variances) and curvature. Methods for dealing with these concerns have been derived and can provide a deeper, more accurate and more nuanced understanding of data. A conceptual basis is provided for understanding when and why standard methods can have poor power and yield misleading measures of effect size. Modern techniques for dealing with known concerns are described and illustrated. Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R Includes an R package with over 1300 functions Includes a solution manual giving detailed answers to all of the exercises This second edition describes many recent advances relevant to basic techniques. For example, a vast array of new and improved methods is now available for dealing with regression, including substantially improved ANCOVA techniques. The coverage of multiple comparison procedures has been expanded and new ANOVA techniques are described. Rand Wilcox is a professor of psychology at the University of Southern California. He is the author of 13 other statistics books and the creator of the R package WRS. He currently serves as an associate editor for five statistics journals. He is a fellow of the Association for Psychological Science and an elected member of the International Statistical Institute.
A Practical Introduction, Second Edition
Author: Rand Wilcox
Publisher: CRC Press
Psychological Testing: A Practical Approach to Design and Evaluation offers a fresh and innovative approach for graduate students and faculty in the fields of testing, measurement, psychometrics, research design, and related areas of study. Author Theresa J.B. Kline guides readers through the process of designing and evaluating a test, while ensuring that the test meets the highest professional standards. The author uses simple, clear examples throughout and fully details the required statistical analyses. Topics include—but are not limited to—design of item stems and responses; sampling strategies; classical and modern test theory; IRT program examples; reliability of tests and raters; validation using content, criterion-related, and factor analytic approaches; test and item bias; and professional and ethical issues in testing.
A Practical Approach to Design and Evaluation
Author: Theresa J.B. Kline
Publisher: SAGE Publications
Category: Social Science
Lecturers - request an e-inspection copy of this text or contact your local SAGE representative to discuss your course needs. Watch Andy Field's introductory video to Discovering Statistics Using R Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world. The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect. Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more. Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
Author: Andy Field,Jeremy Miles,Zoë Field
This is the first book to introduce the new statistics - effect sizes, confidence intervals, and meta-analysis - in an accessible way. It is chock full of practical examples and tips on how to analyze and report research results using these techniques. The book is invaluable to readers interested in meeting the new APA Publication Manual guidelines by adopting the new statistics - which are more informative than null hypothesis significance testing, and becoming widely used in many disciplines. Accompanying the book is the Exploratory Software for Confidence Intervals (ESCI) package, free software that runs under Excel and is accessible at www.thenewstatistics.com. The book’s exercises use ESCI's simulations, which are highly visual and interactive, to engage users and encourage exploration. Working with the simulations strengthens understanding of key statistical ideas. There are also many examples, and detailed guidance to show readers how to analyze their own data using the new statistics, and practical strategies for interpreting the results. A particular strength of the book is its explanation of meta-analysis, using simple diagrams and examples. Understanding meta-analysis is increasingly important, even at undergraduate levels, because medicine, psychology and many other disciplines now use meta-analysis to assemble the evidence needed for evidence-based practice. The book’s pedagogical program, built on cognitive science principles, reinforces learning: Boxes provide "evidence-based" advice on the most effective statistical techniques. Numerous examples reinforce learning, and show that many disciplines are using the new statistics. Graphs are tied in with ESCI to make important concepts vividly clear and memorable. Opening overviews and end of chapter take-home messages summarize key points. Exercises encourage exploration, deep understanding, and practical applications. This highly accessible book is intended as the core text for any course that emphasizes the new statistics, or as a supplementary text for graduate and/or advanced undergraduate courses in statistics and research methods in departments of psychology, education, human development , nursing, and natural, social, and life sciences. Researchers and practitioners interested in understanding the new statistics, and future published research, will also appreciate this book. A basic familiarity with introductory statistics is assumed.
Effect Sizes, Confidence Intervals, and Meta-Analysis
Author: Geoff Cumming
Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians. Providing a conceptual basis for understanding the relative merits and applications of these methods, the book features modern insights and advances relevant to basic techniques in terms of dealing with non-normality, outliers, heteroscedasticity (unequal variances), and curvature. Featuring a guide to R, the book uses R programming to explore introductory statistical concepts and standard methods for dealing with known problems associated with classic techniques. Thoroughly class-room tested, the book includes sections that focus on either R programming or computational details to help the reader become acquainted with basic concepts and principles essential in terms of understanding and applying the many methods currently available. Covering relevant material from a wide range of disciplines, Understanding and Applying Basic Statistical Methods Using R also includes: Numerous illustrations and exercises that use data to demonstrate the practical importance of multiple perspectives Discussions on common mistakes such as eliminating outliers and applying standard methods based on means using the remaining data Detailed coverage on R programming with descriptions on how to apply both classic and more modern methods using R A companion website with the data and solutions to all of the exercises Understanding and Applying Basic Statistical Methods Using R is an ideal textbook for an undergraduate and graduate-level statistics courses in the science and/or social science departments. The book can also serve as a reference for professional statisticians and other practitioners looking to better understand modern statistical methods as well as R programming. Rand R. Wilcox, PhD, is Professor in the Department of Psychology at the University of Southern California, Fellow of the Association for Psychological Science, and an associate editor for four statistics journals. The author of more than 320 articles published in a variety of statistical journals, he is also the author eleven other books on statistics. Dr. Wilcox is creator of WRS (Wilcox’ Robust Statistics), which is an R package for performing robust statistical methods. His main research interest includes statistical methods, particularly robust methods for comparing groups and studying associations.
Author: Rand R. Wilcox
Publisher: John Wiley & Sons
Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.
A Practical Introduction to Statistics using R
Author: R. H. Baayen
Publisher: Cambridge University Press
Category: Language Arts & Disciplines
STATISTICAL METHODS FOR PSYCHOLOGY surveys the statistical techniques commonly used in the behavioral and social sciences, particularly psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasizes conceptual understanding. This Eighth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment. New and expanded topics--reflecting the evolving realm of statistical methods--include effect size, meta-analysis, and treatment of missing data. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
Author: David C. Howell
Publisher: Cengage Learning
"Advanced Statistics in Research: Reading, Understanding, and Writing Up Data Analysis Results" is the simple, nontechnical introduction to the most complex multivariate statistics presented in empirical research articles. "wwwStatsInResearch.com, " is a companion website that provides free sample chapters, exercises, and PowerPoint slides for students and teachers. A free 600-item test bank is available to instructors. "Advanced Statistics in Research" does not show how to "perform" statistical procedures--it shows how to read, understand, and interpret them, as they are typically presented in journal articles and research reports. It demystifies the sophisticated statistics that stop most readers cold: multiple regression, logistic regression, discriminant analysis, ANOVA, ANCOVA, MANOVA, factor analysis, path analysis, structural equation modeling, meta-analysis--and more. "Advanced Statistics in Research" assumes that you have never had a course in statistics. It begins at the beginning, with research design, central tendency, variability, z scores, and the normal curve. You will learn (or re-learn) the big-three results that are common to most procedures: statistical significance, confidence intervals, and effect size. Step-by-step, each chapter gently builds on earlier concepts. Matrix algebra is avoided, and complex topics are explained using simple, easy-to-understand examples. "Need help writing up your results?" Advanced Statistics in Research shows how data-analysis results can be summarized in text, tables, and figures according to APA format. You will see how to present the basics (e.g., means and standard deviations) as well as the advanced (e.g., factor patterns, post-hoc tests, path models, and more). "Advanced Statistics in Research" is appropriate as a textbook for graduate students and upper-level undergraduates (see supplementary materials at StatsInResearch.com). It also serves as a handy shelf reference for investigators and all consumers of research.
Reading, Understanding, and Writing Up Data Analysis Results
Author: Larry Hatcher
Publisher: Shadow Finch Media LLC
Category: Mathematical statistics
This workbook designed to accompany Shaughnessy/Zechmeister, RESEARCH METHODS IN PSYCHOLOGY, 4/e provides students with concrete examples of abstract ideas and gives students the kinds of practical experiences that aid understanding of research methods. The workbook offers instructors brief descriptions of published research in psychology related to the methods covered in each chapter of the text. The brief descriptions are then used as the basis for related questions, problems, and exercises. Instructors can use these exercises as homework assignments or as the basis for in-class discussion.
Author: Eugene B. Zechmeister,John J. Shaughnessy,Jeanne S. Zechmeister
Publisher: McGraw-Hill Humanities Social
Chances Are is the first book to make statistics accessible to everyone, regardless of how much math you remember from school.
The Only Statistic Book You'll Ever Need
Author: Steve Slavin
Publisher: Madison Books
The second edition of Haslam and McGarty's best-selling textbook, Research Methods and Statistics in Psychology, provides students with a highly readable and comprehensive introduction to conducting research in psychology. The book guides readers through the range of choices involved in design, analysis, and presentation and is supplemented by a range of practical learning features both inside the book and online. These draw on the authors' extensive experience as frontline researchers, and provide step-by-step guides to quantitative and qualitative methods and analyses. Written in an accessible and engaging style, this text encourages deep engagement with its subject matter and is designed to inspire students to feel passionate for the research process as a whole. This second edition offers: A comprehensive guide to the process of conducting psychological research from the ground up — covering multiple methodologies, experimental and survey design, data analysis, ethics, and report writing An extensive range of quantitative methods together with detailed step-by-step guides to running analyses using SPSS Extended coverage of qualitative methods ‘Research Bites’ in every chapter: thought-provoking examples of issues raised by contemporary society and research An extensive range of additional learning aids in the textbook to help reinforce learning and revision A host of on-line resources for instructors and students available on publication at www.sagepub.co.uk/haslamandmcgarty2e. Electronic inspection copies are available for instructors.
Author: S Alexander Haslam,Craig McGarty
This text follows the basic structure underlying any research project, starting with decisions about topic choice and progessing the competent handling of complex data, to using the SPSS statistical package. The emphasis is on understanding the concepts of any analysis undertaken, rather than knowing precisely how to do correct mathematical calculations. Features include: quotations from students reflecting their fears and concerns; illustrative boxes showing relevant examples; and a flowchart and navigation guide to individual chapter contents allowing students to access material easily at any point in the text.
A Practical Introduction
Author: R. A. McQueen,Christina Knussen
Publisher: Prentice Hall
A comprehensive introductory research methods guide, this textbook provides students with an understanding of the concepts and techniques of qualitative and quantitative research. It uses simple examples and practice exercises to demystify complex theories and methodologies. Features include: · STQ's - Self Testing Questions (and answers) · Summaries, suggestions for further reading, examples and case studies for each chapter · Consideration of the ethics of research · Comprehensive coverage of quantitative methods, qualitative methods and survey methods . Hints on how to use of the leading software packages for quantitative and qualitative research, SPSS and NUD·
Author: Robert B Burns
Publisher: SAGE Publications Limited
Category: Social Science
Statistics for Research in Psychology by Rick Gurnsey offers an intuitive approach to statistics based on estimation for interpreting research in psychology. This innovative text covers topic areas in a traditional sequence but gently shifts the focus to an alternative approach using estimation, emphasizing confidence intervals, effect sizes, and practical significance, with the advantages naturally emerging in the process. Frequent opportunities for practice and step-by-step instructions for using Excel, SPSS, and R in appendices will help readers come away with a better understanding of statistics that will allow them to more effectively evaluate published research and undertake meaningful research of their own.
A Modern Approach Using Estimation
Author: Frederick (Rick) Norman Gurnsey,Rick Gurnsey
Publisher: SAGE Publications
Offering a clear introduction to the basics of psychological testing as well as to psychometrics and statistics, Foundations of Psychological Testing: A Practical Approach, Fifth Edition by Leslie A. Miller and Robert L. Lovler is a practical book that includes discussion of foundational concepts and issues, using real-life examples and situations that students will easily recognize, relate to, and find interesting. A variety of pedagogical tools further the conceptual understanding needed for effective use of tests and test scores. Now aligned with the 2014 Standards for Educational and Psychological Testing, the Fifth Edition offers new and expanded content throughout.
A Practical Approach
Author: Leslie A. Miller,Robert L. Lovler
Publisher: SAGE Publications