Statistical Reasoning in Psychology and Education, Student's Study Guide and Workbook


Book Description

Develops statistical concepts, understanding of statistical logic, properties regarding statistical devices, assumptions underlying statistical tools and considers what happens when statistical theory meets real-world problems. Emphasizes the statistics of measurement and the interplay of statistics with experimental design, giving full treatment to both inferential and descriptive statistics. New to this edition are realistic examples and numerous original problems with data sets. Special boxed sections introduce students to controversial, topical and current issues such as the bootstrap, meta-analysis.




Statistical Reasoning in Psychology and Education, Workbook


Book Description

Provides students of psychology, education, and behavioral science with an introduction to statistics which emphasizes the relationship between statistical theory and the reality of research. Fosters an understanding of fundamental properties and uses of elementary techniques, appealing to intuitive understanding and common experience. Develops the merit of a statistical approach on logical, rather than mathematically sophisticated, grounds.




Statistical Reasoning in Psychology and Education


Book Description

Develops statistical concepts, understanding of statistical logic, properties regarding statistical devices, assumptions underlying statistical tools and considers what happens when statistical theory meets real-world problems. Emphasizes the statistics of measurement and the interplay of statistics with experimental design, giving full treatment to both inferential and descriptive statistics. New to this edition are realistic examples and numerous original problems with data sets. Special boxed sections introduce students to controversial, topical and current issues such as the bootstrap, meta-analysis.







Learning From Data


Book Description

Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to helpstudents better understand relevant data that affecttheir everyday lives. Numerous examples based on current research and events are featured throughout.To facilitate learning, authors Glenberg and Andrzejewski: Devote extra attention to explaining the more difficult concepts and the logic behind them Use repetition to enhance students’ memories with multiple examples, reintroductions of the major concepts, and a focus on these concepts in the problems Employ a six-step procedure for describing all statistical tests from the simplest to the most complex Provide end-of-chapter tables to summarize the hypothesis testing procedures introduced Emphasizes how to choose the best procedure in the examples, problems and endpapers Focus on power with a separate chapter and power analyses procedures in each chapter Provide detailed explanations of factorial designs, interactions, and ANOVA to help students understand the statistics used in professional journal articles. The third edition has a user-friendly approach: Designed to be used seamlessly with Excel, all of the in-text analyses are conducted in Excel, while the book’s downloadable resources contain files for conducting analyses in Excel, as well as text files that can be analyzed in SPSS, SAS, and Systat Two large, real data sets integrated throughout illustrate important concepts Many new end-of-chapter problems (definitions, computational, and reasoning) and many more on the companion CD Online Instructor’s Resources includes answers to all the exercises in the book and multiple-choice test questions with answers Boxed media reports illustrate key concepts and their relevance to realworld issues The inclusion of effect size in all discussions of power accurately reflects the contemporary issues of power, effect size, and significance. Learning From Data, Third Edition is intended as a text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.







Student Study Guide to Accompany Statistics Alive!


Book Description

This affordable student study guide and workbook to accompany Wendy J. Steinberg and Matthew Price’s Statistics Alive!, Third Edition, helps students get the added review and practice they need to improve their skills and master their Introduction to Statistics course. Bundle and SAVE! Student Study Guide to Accompany Statistics Alive!, Third Edition + Main Text ISBN: 978-1-0718-3088-8







Student Guide for Shavelson Statistical Reasoning for the Behavioral Sciences


Book Description

According to Richard Shavelson, the goal of any good statistics book is for readers not only to learn the meaning of statistical concepts but also to be able to use these concepts to solve problems. This new, revised edition of Statistical Reasoning is written with a two-pronged objective: conceptual and procedural knowledge of statistics.




Statistical Reasoning in the Behavioral Sciences


Book Description

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. The sixth edition includes new information about the use of computers in statistics and offers screenshots of IBM SPSS (formerly SPSS) menus, dialog boxes, and output in selected chapters without sacrificing any of the conceptual logic and the statistical formulas needed to facilitate understanding. The example problems have been updated to reflect more current topics (e.g., text messaging while driving, violence in the media). The latest research and new photos have been integrated throughout the text to make the material more accessible. With these changes, 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.