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.
Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to help students better understand relevant data that affect their 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 memory 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. Emphasize how to choose the best procedure, with a discussion of procedure choice in the examples, problems that require choosing the procedure, and endpapers that provide guidelines for choosing procedures. Focus on power with a separate chapter and power analyses procedures in each chapter. Discuss the rationale for why emphasizing random sampling from populations is emphasized in the classroom but not in actual experiments. Provide detailed explanations of factorial designs, interactions, and ANOVA to help students understand the statistics used in professional journal articles. The new edition features a more user-friendly approach: Designed to be used seamlessly with Excel, all of the in-text analyses are conducted in Excel, while the book's CD contains 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 one focusing on the effectiveness of Zyban and gum on smoking and the other on the effects of children on marriage
This fully updated fourth edition explores the foundations of statistical reasoning, focusing on how to interpret psychological data and statistical results. This edition includes three important new features. First, the book is closely integrated with the free statistical analysis program JASP. Thus, students learn how to use JASP to help with tasks such as constructing grouped frequency distributions, making violin plots, conducting inferential statistical tests, and creating confidence intervals. Second, reflecting the growing use of Bayesian analyses in the professional literature, this edition includes a chapter with an introduction to Bayesian statistics (also using JASP). Third, the revised text incorporates adjunct questions, that is, questions that challenge the student’s understanding, after each major section. Cognitive psychology has demonstrated how adjunct questions and related techniques such as self-explanation can greatly improve comprehension. Additional key features of the book include: • A user-friendly approach, with focused attention to explaining the more difficult concepts and the logic behind them. End of chapter tables summarize the hypothesis testing procedures introduced, and exercises support information recall and application. • The consistent use of a six-step procedure for all hypothesis tests that captures the logic of statistical inference. • Multiple examples of each of the major inferential statistical tests. • Boxed media reports illustrate key concepts and their relevance to real-world issues. • A focus on power, with a separate chapter, and power analysis procedures in each chapter. With comprehensive digital resources, including large data sets integrated throughout the textbook, and files for conducting analysis in JASP, this is an essential text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.
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.
Focuses on how to interpret psychological data and statistical results. This book reviews the basics of statistical reasoning to help students better understand relevant data that affect their everyday lives. It is provided with numerous examples based on research and events.
Knowledge representation is fundamental to the study of mind. All theories of psychological processing are rooted in assumptions about how information is stored. These assumptions, in turn, influence the explanatory power of theories. This book fills a gap in the existing literature by providing an overview of types of knowledge representation techniques and their use in cognitive models. Organized around types of representations, this book begins with a discussion of the foundations of knowledge representation, then presents discussions of different ways that knowledge representation has been used. Both symbolic and connectionist approaches to representation are discussed and a set of recommendations about the way representations should be used is presented. This work can be used as the basis for a course on knowledge representation or can be read independently. It will be useful to students of psychology as well as people in related disciplines--computer science, philosophy, anthropology, and linguistics--who want an introduction to techniques for knowledge representation.
This fully updated fourth edition explores the foundations of statistical reasoning, focusing on how to interpret psychological data and statistical results. This edition includes three important new features. First, the book is closely integrated with the free statistical analysis program JASP. Thus, students learn how to use JASP to help with tasks such as constructing grouped frequency distributions, making violin plots, conducting inferential statistical tests, and creating confidence intervals. Second, reflecting the growing use of Bayesian analyses in the professional literature, this edition includes a chapter with an introduction to Bayesian statistics (also using JASP). Third, the revised text incorporates adjunct questions, that is, questions that challenge the student’s understanding, after each major section. Cognitive psychology has demonstrated how adjunct questions and related techniques such as self-explanation can greatly improve comprehension. Additional key features of the book include: • A user-friendly approach, with focused attention to explaining the more difficult concepts and the logic behind them. End of chapter tables summarize the hypothesis testing procedures introduced, and exercises support information recall and application. • The consistent use of a six-step procedure for all hypothesis tests that captures the logic of statistical inference. • Multiple examples of each of the major inferential statistical tests. • Boxed media reports illustrate key concepts and their relevance to real-world issues. • A focus on power, with a separate chapter, and power analysis procedures in each chapter. With comprehensive digital resources, including large data sets integrated throughout the textbook, and files for conducting analysis in JASP, this is an essential text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.
This important, research-based text explores the concept of literacy as social practice within diverse family, community and educational settings. Its theoretical premise that literacy learning and life chances are inextricably linked is underscored by practical example, teachers' stories and real-world vignettes.
Design Research in Education is a practical guide containing all the information required to begin a design research project. Providing an accessible background to the methodological approaches used in design research as well as addressing all the potential issues that early career researchers will encounter, the book uniquely helps the early career researcher to gain a full overview of design research and the practical skills needed to get their project off the ground. Based on extensive experience, the book also contains multiple examples of design research from both undergraduate and postgraduate students, to demonstrate possible projects to the reader. With easy to follow chapters and accessible question and response sections, Design Research in Education contains practical advice on a wide range of topics related to design research projects including: The theory of design research, what it entails, and when it is suitable The formulation of research questions How to structure a research project The quality of research and the methodological issues of validity and reliability How to write up your research The supervision of design research. Through its theoretical grounding and practical advice, Design Research in Education is the ideal introduction into the field of design based research and is essential reading for bachelor's, master's and PhD students new to the field, as well as to supervisors overseeing projects that use design research.
The Psychology of Human Memory presents a comprehensive discussion on the principles of human memory. The book is primarily concerned with theories and experiments on the acquisition and use of information. Topics on theoretical ideas that formed the basis for the earliest studies of memory; memory processes; aspects of association theory; capacity limitations; coding processes; types of memories; and applied memory research are also tackled. Psychologists, educators, psychiatrists, and students will find the book a good reference material.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.