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The terrific trio of Arthur Aron, Elaine N. Aron, and Elliot Coups collaborate to present a phenomenal introductory textbook for students in their work Statistics for Psychology (5th Edition), ISBN 9780136010579. Serving as an understandable and appealing guide to the concepts encompassing statistics, this text boasts innovative features and methodologies...
The terrific trio of Arthur Aron, Elaine N. Aron, and Elliot Coups collaborate to present a phenomenal introductory textbook for students in their work Statistics for Psychology (5th Edition), ISBN 9780136010579. Serving as an understandable and appealing guide to the concepts encompassing statistics, this text boasts innovative features and methodologies to help students grasp every facet through the lens of psychology. This most recent edition incorporates definitional formulas to guide students to a thorough comprehension of content. Each procedure is taught with verbal and numerical strategies which reinforce concepts as well as emphasize the reasoning behind the material that students are learning. Other revisions boasted in this book include new coverage of content, various practice examples, as well as a guide taking students from basic procedures through the analysis of variance (ANOVA). Thanks to the all-inclusive nature and coverage of this book, university and college students will experience success in their endeavors involving reading and interpreting current research. Arthur Aron, Elaine N. Aron, and Elliot Coups cover the gamut of material in their book Statistics for Psychology (5th Edition). A myriad of concepts are presented including discussion of the two branches of statistical methods, frequency tables, shapes of frequency distributions, central tendency and variability, as well as inferential statistics. Other topics presented in this comprehensive text include probability, Z scores, the hypothesis-testing process, estimation, standard errors, and confidence intervals, decision errors, effect size, and power in research articles, and the t test for a single sample. Information is also devoted to analysis of variance, recognizing and interpreting interaction effects, graphing correlations, the linear prediction rule, as well as rank-order tests.
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