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Applied Multivariate Statistics for the Social Sciences,Used
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Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and datasets from actual research studies. With the added expertise of coauthor Keenan Pituch (University of TexasAustin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally.Features new to this edition include:NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedureNEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this 'newer' procedure and how it can be used in conventional and multilevel settingsNEW Example Results Section writeups that illustrate how results should be presented in research papers and journal articlesNEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete dataCompletely rewritten chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting resultsNEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approachUpdated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3)A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructors resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises).Ideal for advanced graduatelevel courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Prerequisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.
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