Advanced And Multivariate Statistical Methods For Social Science Research

"Unlike other advanced statistical texts, this book combines the theory and practice behind a number of statistical techniques which students of the social sciences need to evaluate, analyze, and test their research hypotheses. Each chapter discusses the purpose, rationale, and assumptions for using each statistical test, rather than focusing on the memorization of formulas. The tests are further elucidated throughout the text by real examples of analysis. Of particular value to students is the book's detailed discussion of how to utilize SPSS to run each test, read its output, interpret, and write the results. Advanced & Multivariate Statistical Methods for Social Science Research is an indispensable resource for students of disciplines as varied as social work, nursing, public health, psychology, and education."--Publisher's website.

Unlike other advanced statistical texts, this book combines the theory and practice behind a number of statistical techniques which students of the social sciences need to evaluate, analyze, and test their research hypotheses. Each chapter discusses the purpose, rationale, and assumptions for using each statistical test, rather than focusing on the memorization of formulas. The tests are further elucidated throughout the text by real examples of analysis. Of particular value to students is the book's detailed discussion of how to utilize SPSS to run each test, read its output, interpret, and write the results. Advanced & Multivariate Statistical Methods for Social Science Research is an indispensable resource for students of disciplines as varied as social work, nursing, public health, psychology, and education. Electronic database files are available for student and instructor use.http: //lyceumbooks.com/StudentResources.htm

Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.

Advanced and Multivariate Statistical Methods, Seventh Edition provides conceptual and practical information regarding multivariate statistical techniques to students who do not necessarily need technical and/or mathematical expertise in these methods. This text has three main purposes. The first purpose is to facilitate conceptual understanding of multivariate statistical methods by limiting the technical nature of the discussion of those concepts and focusing on their practical applications. The second purpose is to provide students with the skills necessary to interpret research articles that have employed multivariate statistical techniques. Finally, the third purpose of AMSM is to prepare graduate students to apply multivariate statistical methods to the analysis of their own quantitative data or that of their institutions. New to the Seventh Edition All references to SPSS have been updated to Version 27.0 of the software. A brief discussion of practical significance has been added to Chapter 1. New data sets have now been incorporated into the book and are used extensively in the SPSS examples. All the SPSS data sets utilized in this edition are available for download via the companion website. Additional resources on this site include several video tutorials/walk-throughs of the SPSS procedures. These "how-to" videos run approximately 5–10 minutes in length. Advanced and Multivariate Statistical Methods was written for use by students taking a multivariate statistics course as part of a graduate degree program, for example in psychology, education, sociology, criminal justice, social work, mass communication, and nursing.

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 data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), 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 procedure NEW 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 settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written 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 results NEW 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 approach Updated 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 instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises) Ideal for advanced graduate-level 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. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.

In Using Statistical Methods, Soleman Abu-Bader detects and addresses the gaps between the research and data analysis of the classroom environment and the practitioner's office. This book not only guides social scientists through different tests, but also provides students and researchers alike with information that will help them in their own practice. With focus on the purpose, rationale, and assumptions made by each statistical test, and a plethora of research examples that clearly display their applicability and function in real-world practice, Professor Abu-Bader creates a step-by-step description of the process needed to clearly organize, choose a test or statistical technique, analyze, interpret, and report research findings.

Tacq demonstrates how a researcher comes to the appropriate choice of a technique for multivariate analysis. He examines a wide selection of topics from a range of disciplines including sociology, psychology, economics, and political science.

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.