Statistical Methods For The Social Sciences Pdf
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📒Using Statistical Methods In Social Science Research ✍ Soleman H. Abu-Bader
✏Using Statistical Methods in Social Science Research Book Summary : 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.
📒Statistical Methods For The Social Sciences ✍ Alan Agresti
✏Statistical methods for the social sciences Book Summary :
📒Research In Practice ✍ Martin Terre Blanche
✏Research in Practice Book Summary : A major shift in research methodology from technical to more contextual and pragmatic approaches, this thorough resource incorporates new trends while also providing comprehensive coverage of the full range of established research approaches and techniques, skillfully combining epistemology, methodology, statistics, and application in a volume that is both sophisticated and practical. Placing a greater emphasis on interdisciplinary and applied research skills, this guide encourages the concurrent use of qualitative and quantitative methods and explores such complex topics as ethical issues in social science research; inferential statistical methods; and Marxist, feminist, and black scholarship perspectives.
📒Statistics For The Social Sciences ✍ Russell T. Warne
✏Statistics for the Social Sciences Book Summary : This introductory undergraduate textbook is the first statistics textbook built around the General Linear Model.
📒Advanced And Multivariate Statistical Methods For Social Science Research ✍ Soleman H. Abu-Bader
✏Advanced and Multivariate Statistical Methods for Social Science Research Book Summary : 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 discussionof how to utilize SPSS to run each test, read its output, interpret, and write the results.Advanced and 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
📒Statistics For Social Sciences With Spss Applications ✍ ASTHANA , HARI SHANKAR
✏STATISTICS FOR SOCIAL SCIENCES WITH SPSS APPLICATIONS Book Summary : Designed as a text for the undergraduate and postgraduate students of psychology, education, sociology, demography and economics, this comprehensive book explains the theoretical and computational aspects of statistics. Since the students of social sciences often find it difficult to comprehend the statistical techniques due to complex mathematical steps involved, this book explains each concept and related statistical derivations or formulae in a simple and clear manner. The text provides solutions to basic concepts and problems using a number of illustrations. In addition, it demonstrates the simplest way of using SPSS software for statistical analysis. SPSS screen images are used to make the ideas more clear to the readers. This is preceded by theoretical details and solved examples so that even those having minimal knowledge of computer can use SPSS easily and comprehend the complex intermediate steps involved in statistical analysis. Besides the undergraduate and postgraduate students of social sciences, the researchers and professionals in this field should find this book immensely useful. The Second Edition of the book has been prepared on the basis of the feedback received from the readers. As per their demand, a new chapter based on multivariate analysis, i.e., Factor analysis has been introduced. Many other chapters have been modified and updated to make them more effective and simple for the readers. Most importantly, screenshots of the latest version of SPSS have been incorporated in the relevant chapters to keep the students abreast with the developments in tools and techniques of statistics.
📒Propensity Score Analysis ✍ Shenyang Guo
✏Propensity Score Analysis Book Summary : Fully updated to reflect the most recent changes in the field, the Second Edition of Propensity Score Analysis provides an accessible, systematic review of the origins, history, and statistical foundations of propensity score analysis, illustrating how it can be used for solving evaluation and causal-inference problems. With a strong focus on practical applications, the authors explore various strategies for employing PSA, discuss the use of PSA with alternative types of data, and delineate the limitations of PSA under a variety of constraints. Unlike existing textbooks on program evaluation and causal inference, this book delves into statistical concepts, formulas, and models within the context of a robust and engaging focus on application.
📒Nonparametric And Distribution Free Methods For The Social Sciences ✍ Leonard A. Marascuilo
✏Nonparametric and distribution free methods for the social sciences Book Summary :
📒Statistics For The Social Sciences ✍ R . Mark Sirkin
✏Statistics for the Social Sciences Book Summary : Popular in previous editions, this Third Edition continues to help build students' confidence and ability in doing statistical analysis by slowly moving from concepts that require little computational work to those that require more. Author R. Mark Sirkin once again demonstrates how statistics can be used so that students come to appreciate their usefulness rather than fear them. Statistics for the Social Sciences emphasizes the analysis and interpretation of data to give students a feel for how data interpretation is related to the methods by which the information was obtained.
📒Applied Multivariate Statistics For The Social Sciences ✍ James Paul Stevens
✏Applied Multivariate Statistics for the Social Sciences Book Summary : This best-selling text is written for those who use, rather than develop statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than on proving results. Helpful narrative and numerous examples enhance understanding and a chapter on matrix algebra serves as a review. Annotated printouts from SPSS and SAS indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use these packages, 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 book is noted for its extensive applied coverage of MANOVA, its emphasis on statistical power, and numerous exercises including answers to half. The new edition features: New chapters on Hierarchical Linear Modeling (Ch. 15) and Structural Equation Modeling (Ch. 16) New exercises that feature recent journal articles to demonstrate the actual use of multiple regression (Ch. 3), MANOVA (Ch. 5), and repeated measures (Ch. 13) A new appendix on the analysis of correlated observations (Ch. 6) Expanded discussions on obtaining non-orthogonal contrasts in repeated measures designs with SPSS and how to make the identification of cell ID easier in log linear analysis in 4 or 5 way designs Updated versions of SPSS (15.0) and SAS (8.0) are used throughout the text and introduced in chapter 1 A book website with data sets and more. Ideal for courses on multivariate statistics found in psychology, education, sociology, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial ANOVA and covariance. Working knowledge of matrix algebra is not assumed.