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This textbook offers an accessible and comprehensive introduction to statistics for all undergraduate psychology students, but particularly those in their second and third years who have already covered an initial introductory course. It covers all of the key areas in quantitative methods including sampling, significance tests, regression, and multivariate techniques and incorporates a range of exercises and problems at the end of each chapter for the student to follow. The free CD-ROM with tutorial modules complements and enhances the exercises in the text, offers scope for distance learning, and makes both the traditional and non-traditional approaches much more accessible. Key points of the book a
Originally published by Viking Penguin, 2014.
This inexpensive paperback provides a brief, simple overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly. Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated measures ANOVA, and factor analysis. Each chapter begins with a short description of the statistic and when it should be used. This is followed by a more in-depth explanation of how the statistic works. Finally, each chapter ends with an example of the statistic in use, and a sample of how the results of analyses using the statistic might be written up for publication. A glossary of statistical terms and symbols is also included. New features in the third edition include: a new chapter on Factor and Reliability Analysis especially helpful to those who do and/or read survey research, new "Writing it Up" sections demonstrate how to write about and interpret statistics seen in books and journals, a website at http://www.psypress.com/statistics-in-plain-english with PowerPoint presentations, interactive problems (including an overview of the problem's solution for Instructors) with an IBM SPSS dataset for practice, videos of the author demonstrating how to calculate and interpret most of the statistics in the book, links to useful websites, and an author blog, new section on understanding the distribution of data (ch. 1) to help readers understand how to use and interpret graphs, many more examples, tables, and charts to help students visualize key concepts. Statistics in Plain English, Third Edition is an ideal supplement for statistics, research methods, and/or for courses that use statistics taught at the undergraduate or graduate level, or as a reference tool for anyone interested in refreshing their memory about key statistical concepts. The research examples are from psychology, education, and other social and behavioral sciences.
The current construct of intellectual disability is based on the assumption that both IQ and adaptive behaviour can be measured accurately. Intellectual Disability explains how and why this is not fit for purpose and that it is actually neither necessary nor reasonable to have a single construct of intellectual disability.
This book provides a comprehensive introduction to psychological assessment and covers areas not typically addressed in existing test and measurements texts, such as neuropsychological assessment and the use of tests in forensics settings. The book introduces the vocabulary of the profession and the most basic mathematics of testing early as being fundamental to understanding the field. Numerous examples are drawn from tests that the authors have written or otherwise helped to develop, reflecting the authors’ deep understanding of these tests and their familiarity with problems encountered in test development, use, and interpretation. Following the introduction of the basic areas of psychometrics, the book moves to areas of testing that represent various approaches to measuring different psychological constructs (memory, language, executive function, etc.), with emphasis on the complex issue of cultural bias in testing. Examples of existing tests are given throughout the book; however, this book is not designed to prepare students to go out and administer, score, and interpret specific psychological tests. Rather, the purpose of this book is to provide the foundational core of knowledge about tests, measurement, and assessment constructs, issues, and quantitative tools. Explains what constitutes a psychological test, how tests are developed, how they are best used, and how to evaluate their strengths and weaknesses; Describes areas of testing that represent different approaches to measuring different psychological constructs; Explains applications of psychological testing to issues in the courts; Addresses how test authors and publishers design and research tests to address the difficult and demanding issues of cultural differences in test performance and interpretation of test results.
The SAGE Handbook of Survey Development and Application provides a practical resource that researchers can go to for cutting-edge tools to ensure they are employing the best survey research techniques. This handbook not only covers the classic and innovational skills and approaches involved at every step of the survey research process, but also centres itself around applied, how-to guidance to aid readers in best practice. Chapters engage with a broad range of topics including sampling issues, approaches to establishment of measurement equivalence, and the use of online labour pools in survey development. With contributions from a global community of leading and emerging scholars across a wide variety of disciplines, this Handbook is focused on being applicable and accessible across the social sciences. Containing over 120 tables and figures, checklists and tutorial guides, The SAGE Handbook of Survey Development and Application will serve as a one stop resource for survey research. This handbook serves as a touchstone for a variety of fields such as Organizational Behavior, Industrial & Organizational Psychology, Management, Psychology, Educational Research, Marketing, Public Policy, and others. PART 1: Conceptual Issues and Operational Definition PART 2: Research Design Considerations PART 3: Item Development PART 4: Scale Improvement Methods PART 5: Data Collection PART 6: Data Management and Analysis PART 7: Research Production and Dissemination PART 8: Applications