Applied Multivariate Statistics for the Social Sciences - Tapa blanda

Críticas

"In summary, this book will appeal to graduate students in a variety of disciplines including psychology, education, business, and management. It is an excellent text that could be used in courses on multivariate analysis that are targeted toward students who probably do not have a Master's degree in mathematics or statistics...Topics are explained clearly and the examples and explanations of results make the techniques described therein understandable. I particularly appreciated the emphasis on power, evaluation of assumptions, cross-validation, and concerns about capitalization on chance."
―Organizational Research Methods

"The book is sprinkled with practical advice that researchers will find useful when applying these techniques to their work....Beginning users of multivariate statistics will appreciate the detailed examples from the social-science literature that include annotated output....Stevens does an excellent job of conveying how multivariate statistics is currently performed in the social sciences, with advice along the way on how to improve the status quo."
―The American Statistician

"...Dr. Stevens writes so clearly. My students tell me in unsolicited comments that his text is helpful in developing their understanding. The material is presented in an informative and engaging manner."
―Gary J. Lautenschlager
University of Georgia

"The liberal inclusion of data examples using such packages as SAS and SPSS is especially helpful to the students."
―Daniel D. Blaine
University of Hawaii at Manoa

Reseña del editor

This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.