Introduction To Behavioral Research Methods

Leary uses variability as an integrative theme, covering both experimental and non-experimental methods, including advanced topics.

Rigorous, yet readable. The author presents the material with sufficient elaboration, explanation, and examples that not only interest the student, but make it understandable. Introduction to Behavioral Research Methods incorporates the four basic approaches to behavioral research (descriptive research, correlational research, experimental research, and quasi-experimental research), and shows students how to conceptualise questions, measure variables, design studies, and analyse data. Chapters on research ethics and scientific writing (including the most recent version of APA style) round out the book. Throughout each chapter, boxes on “Developing Your Research Skills” and “Behavioral Research Case Study” provide practical examples and pique student interest. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.

Title on accompanying CD-ROM: Behavioral research on the Internet.

MATLAB is a powerful data analysis program, but many behavioral science researchers find it too daunting to learn and use. An Introduction to MATLAB for Behavioral Researchers by Christopher R. Madan is an easy-to-understand, hands-on guide for behavioral researchers who have no prior programming experience. Written in a conversational and non-intimidating style, the author walks students—step by step—through analyzing real experimental data. Topics covered include the basics of programming, the implementation of simple behavioral analyses, and how to make publication-ready figures. More advanced topics such as pseudo-randomization of trial sequences to meet specified criteria and working with psycholinguistic data are also covered. Interesting behavioral science examples and datasets from published studies, such as visualizing fixation patterns in eye-tracking studies and animal search behavior in two-dimensional space, help develop an intuition for data analysis, which is essential and can only be developed when working with real research problems and real data.