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Behavioral Sciences Medical Books Free

Copyright: 2013, format: Hardcover, availability: In Stock, availability: Out of Stock, availability: Preorder, this product is out of stock, and cannot be ordered online at the moment. To place an order or to receive additional ordering information, please call the Order Department at.

Alternatives to Significance Testing Replication and Meta-Analysis Bayesian Estimation and Best Practices Summary References Index About the Author Author Bio Rex B. Kline, PhD, is a professor of psychology at Concordia University in Montral, Canada. Table of Contents, acknowledgments. Introduction, i. Fundamental Concepts, changing Times, sampling and Estimation, logic and Illogic of Significance Testing, cognitive Distortions in Significance Testing. II. Effect Size Estimation in Comparative Studies, continuous Outcomes, categorical Outcomes, single-Factor Designs Multifactor Designs III. Enter your mobile number or email address below and we'll send you a link to download the free Kindle App. Then you can start reading Kindle books on your smartphone, tablet, or computer - no Kindle device required. As more and more people become aware of this problem, the emphasis on statistical significance in the reporting of results is declining. Increasingly, researchers are expected to describe the magnitudes and precisions of their findings and also their practical, theoretical, or clinical significance. He has a doctorate in clinical psychology. His areas of research and writing include the psychometric evaluation of cognitive abilities, cognitive and scholastic assessment of children, structural equation modeling, the training of behavioral science researchers, and usability engineering in computer science. Home publications Databases aPA Books beyond Significance Testing, Second. List Price: 59.95, member/Affiliate Price: 49.95, quantity:, fREE Shipping. For individuals in the U.S. U.S. Territories, pages: 349, item 4316151, iSBN: -1. Overview, traditional education in statistics that emphasizes significance testing leaves researchers and students ill prepared to understand what their results really mean. Specifically, most researchers and students who do not have strong quantitative backgrounds have difficulty understanding outcomes of statistical tests.