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Cited by more than 300 scholars, Statistical Reasoning in the Behavioral Sciences continues to provide streamlined resources and easy-to-understand information on statistics in the behavioral sciences and related fields, including psychology, education, human resources management, and sociology. Students and professionals in the behavioral sciences will develop an understanding of statistical logic and procedures, the properties of statistical devices, and the importance of the assumptions underlying statistical tools. This revised and updated edition continues to follow the recommendations of the APA Task Force on Statistical Inference and greatly expands the information on testing hypotheses about single means. The Seventh Edition moves from a focus on the use of computers in statistics to a more precise look at statistical software. The “Point of Controversy” feature embedded throughout the text provides current discussions of exciting and hotly debated topics in the field. Readers will appreciate how the comprehensive graphs, tables, cartoons and photographs lend vibrancy to all of the material covered in the text.
Over the past 49 years, Statistical Reasoning in the Behavioral Sciences has provided students and professionals in psychology, education, sociology, human resources management, and related fields with a comprehensive understanding of statistical logic and procedures. Now in its Seventh Edition, this revised and updated text offers streamlined coverage based on current research and practices to help students master statistical devices and their underlying assumptions. Statistical procedures are introduced first through a description of their essential logic, then demonstrated using raw data and hand calculations to reinforce central ideas; SPSS tutorials are then used to confirm results, allowing students to master this powerful software package while developing a solid understanding of each problem’s underlying mechanisms. Coverage of current issues highlights the field’s dynamic evolution, while conversational discussion relates statistics to experimental design and what happens when strict statistical theory merges with real-world data. Cited by researchers nearly 1,000 times over the years, this book presents essential statistical concepts in a user-friendly format that eases teaching and learning while facilitating long-term retention.
Fundamentals of Statistical Reasoning in Education 4th Edition, like the first three editions, is written largely with students of education in mind. Accordingly, Theodore Coladarci and Casey D. Cobb have drawn primarily on examples and issues found in school settings, such as those having to do with instruction, learning, motivation, and assessment. The emphasis on educational applications notwithstanding, the authors are confident that readers will find Fundamentals of Statistical Reasoning in Education 4th Edition of general relevance to other disciplines in the behavioral sciences as well. The 4th Edition of Fundamentals is still designed as a “one semester” book. The authors intentionally sidestep topics that few introductory courses cover (e.g., factorial analysis of variance, repeated measures analysis of variance, multiple regression). At the same time, effect size and confidence intervals are incorporated throughout, which today are regarded as essential to good statistical practice.
Exploring the intersection of ethics and statistics, this comprehensive guide illustrates the proper use of probabilistic and statistical reasoning in the behavioral, social, and biomedical sciences. Lauded for their contributions to statistics, psychology, and psychometrics, the authors make statistical methods relevant to readers' day-to-day lives by including real historical situations that demonstrate the role of statistics in reasoning and decision making. In addition, seven U.S. Supreme Court decisions reflect the influence of statistical and psychometric reasoning and interpretation/misinterpretation.
Statistical Power Analysis is a nontechnical guide to power analysis in research planning that provides users of applied statistics with the tools they need for more effective analysis. The Second Edition includes: * a chapter covering power analysis in set correlation and multivariate methods; * a chapter considering effect size, psychometric reliability, and the efficacy of "qualifying" dependent variables and; * expanded power and sample size tables for multiple regression/correlation.
For courses in Statistical Literacy A qualitative approach teaches students how to reason using statistics Understanding the core ideas behind statistics is crucial to everyday success in the modern world. Statistical Reasoning for Everyday Life is designed to teach these core ideas through real-life examples so that students are able to understand the statistics needed in their college courses, reason with statistical information in their careers, and to evaluate and make everyday decisions using statistics. The authors approach each concept qualitatively, using computation techniques only to enhance understanding and build on ideas step-by-step, working up to real examples and complex case studies. The Fifth Edition has been revised to update many exercises, examples, and case studies to engage today’s students with the latest data and relevant topics. Also available with MyLab Statistics MyLab™ Statistics is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. NOTE: You are purchasing a standalone product; MyLab Statistics does not come packaged with this content. If you would like to purchase both the physical text and MyLab Statistics, search for: 0134701364 / 9780134701363 Statistical Reasoning for Everyday Life Plus NEW MyLab Statistics with Pearson eText -- Access Card Package, 5/e Package consists of: 0134494040 / 9780134494043 Statistical Reasoning for Everyday Life 0134678524 / 9780134678528 MyLab Statistics with Pearson eText -- Standalone Access Card -- for Statistical Reasoning for Everyday Life 0134678559 / 9780134678559 MyLab Statistics-- Royalty Bearing Content -- for Statistical Reasoning for Everyday Life
This book examines two questions: Do people make use of abstract rules such as logical and statistical rules when making inferences in everyday life? Can such abstract rules be changed by training? Contrary to the spirit of reductionist theories from behaviorism to connectionism, there is ample evidence that people do make use of abstract rules of inference -- including rules of logic, statistics, causal deduction, and cost-benefit analysis. Such rules, moreover, are easily alterable by instruction as it occurs in classrooms and in brief laboratory training sessions. The fact that purely formal training can alter them and that those taught in one content domain can "escape" to a quite different domain for which they are also highly applicable shows that the rules are highly abstract. The major implication for cognitive science is that people are capable of operating with abstract rules even for concrete, mundane tasks; therefore, any realistic model of human inferential capacity must reflect this fact. The major implication for education is that people can be far more broadly influenced by training than is generally supposed. At high levels of formality and abstraction, relatively brief training can alter the nature of problem-solving for an infinite number of content domains.
This book describes an approach to understanding, modeling, and improving the probabilistic reasoning of ordinary adults, comparing their reasoning to that of "experts." For specialists in judgment and decision making and all cognitive scientists.
A New Approach to Sound Statistical ReasoningInferential Models: Reasoning with Uncertainty introduces the authors' recently developed approach to inference: the inferential model (IM) framework. This logical framework for exact probabilistic inference does not require the user to input prior information. The authors show how an IM produces meaning
Nolan and Heinzen’s engaging introduction to statistics has captivated students with its easy readability and vivid examples drawn from everyday life. The mathematics of statistical reasoning are made accessible with careful explanations and a helpful three-tier approach to working through exercises: Clarifying the Concepts, Calculating the Statistics, and Applying the Concepts. New pedagogy, end-of-chapter material, and the groundbreaking learning space StatsPortal give students even more tools to help them master statistics than ever before.