Author: Vicki F. Sharp
Publisher: Little Brown & Co
This introductory undergraduate textbook is the first statistics textbook built around the General Linear Model.
Author: Russell T. Warne
Publisher: Cambridge University Press
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.
Author: James Paul Stevens
Publisher: Taylor & Francis
Category: Social Science
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.
Analyses with SAS and IBM’s SPSS, Sixth Edition
Author: Keenan A. Pituch,James P. Stevens
With Computer Applications
Author: Anthony Walsh
Publisher: Harpercollins College Division
Category: Social Science
Book & CD-ROM. This tutorial-based programme addresses some of the problems involved in teaching statistics to undergraduate social science students. These include the huge difference in ability among students, large classes that do not facilitate problem-based question-and-answer lecturing format, and a general resistance to statistics. The text emphasises contemporary approaches to data analysis, the role of statistics in sampling, and the idea that inference depends upon how sampling is conducted. The question of how one ensures that data is sound is explored with reference to measurement issues and test construction. It encourages problem-solving by getting students to go through worked examples and presenting open-ended problems and discussion questions.
A Course in Statistics for the Social Sciences
Author: Kevin Durrheim,Colin Tredoux
Publisher: Juta and Company Ltd
Category: Social Science
Bridging the gap between traditional classical statistics and a Bayesian approach, David Kaplan provides readers with the concepts and practical skills they need to apply Bayesian methodologies to their data analysis problems. Part I addresses the elements of Bayesian inference, including exchangeability, likelihood, prior/posterior distributions, and the Bayesian central limit theorem. Part II covers Bayesian hypothesis testing, model building, and linear regression analysis, carefully explaining the differences between the Bayesian and frequentist approaches. Part III extends Bayesian statistics to multilevel modeling and modeling for continuous and categorical latent variables. Kaplan closes with a discussion of philosophical issues and argues for an "evidence-based" framework for the practice of Bayesian statistics. User-Friendly Features *Includes worked-through, substantive examples, using large-scale educational and social science databases, such as PISA (Program for International Student Assessment) and the LSAY (Longitudinal Study of American Youth). *Utilizes open-source R software programs available on CRAN (such as MCMCpack and rjags); readers do not have to master the R language and can easily adapt the example programs to fit individual needs. *Shows readers how to carefully warrant priors on the basis of empirical data. *Companion website features data and code for the book's examples, plus other resources.
Author: David Kaplan
Publisher: Guilford Publications
Designed for introductory-level statistics courses, Understanding Statistics for the Social Sciences, Criminal Justice, and Criminology presents the fundamentals of statistics in a clear and simplified format. This accessible text addresses all of the basics of statistical analysis while still providing the reader with the larger view of statistics. The authors focus on calculating the basic formulas yet preserve enough advanced material to prepare the student for further study. The book also provides information on deciding when to use particular statistical analyses, how to input and analyze data through programs such as Microsoft Excel and SPSS, the interpretation of statistical output, and making conclusions based on those results. The student-friendly and simplified presentation of Understanding Statistics makes it the ideal introductory statistics text and will provide readers with a strong foundation in statistics – conceptually and pragmatically. Understanding Statistics for the Social Sciences, Criminal Justice, and Criminology boasts a variety of in-text study aids, such as key terms, equation summaries, exercises, end-of-chapter references, and suggested readings, and an equation glossary; as well as a collection of online study tools housed on the dedicated student companion website. The student-friendly presentation of the material coupled with the rich variety of student and instructor resources make Understanding Statistics the ideal introductory statistics text for undergraduate students! Every new printed copy is packaged with full access to the student companion website featuring a a rich variety of study tools! (eBook version does not include access to the student companion website. Standalone access can be purchased here http://www.jblearning.com/catalog/9781449649234/) Student Resources: -Microsoft and Excel SPSS data sets -Companion website featuring: *interactive flashcards *interactive glossary *practice quiz (with answers) *student data sets, in Excel and SPSS, that correlate to the chapter material *weblinks
Author: Jeffery T. Walker,Sean Maddan
Publisher: Jones & Bartlett Publishers
This basic social science statistics text uses illustrations and exercises for sociology, social work, political science, and criminal justice. Praised for a writing style that takes the anxiety out of statistics courses, the author explains basic statistical principles through a variety of engaging exercises, each designed to illuminate the unique theme of examining society both creatively and logically. In an effort to make the study of statistics relevant to students of the social sciences, the author encourages readers to interpret the results of calculations in the context of more substantive social issues, while continuing to value precise and accurate research.
Author: Ferris Ritchey
Publisher: McGraw-Hill Education
Category: Social Science
Author: Vicki F. Sharp
Category: Social sciences
Author: Thomas Gerard Connolly,Wladyslaw Sluckin
Introductory Statistics for the Social and Health Sciences.
Author: Victoria L. Mantzopoulos
Aimed at undergraduate students taking course in statistics for sociology and the social sciences, this work assumes only high school algebra. This edition features a more applied social science perspective, especially with regard to multivariate analysis and the interpretation of results.
A Tool for the Social Sciences
Publisher: Wadsworth Publishing Company
Author: Frederick D. Herzon,Michael Hooper
Master the essential statistical skills used in social andbehavioral sciences Essentials of Statistics for the Social and Behavioral Sciencesdistills the overwhelming amount of material covered inintroductory statistics courses into a handy, practical resourcefor students and professionals. This accessible guide covers basicto advanced concepts in a clear, concrete, and readablestyle. Essentials of Statistics for the Social and Behavioral Sciencesguides you to a better understanding of basic concepts ofstatistical methods. Numerous practical tips are presented forselecting appropriate statistical procedures. In addition, thisuseful guide demonstrates how to evaluate and interpret statisticaldata, provides numerous formulas for calculating statistics fromtables of summary statistics, and offers a variety of workedexamples. As part of the Essentials of Behavioral Science series, this bookoffers a thorough review of the most relevant statistical conceptsand techniques that will arm you with the tools you'll need forknowledgeable, informed practice. Each concise chapter featuresnumerous callout boxes highlighting key concepts, bulleted points,and extensive illustrative material, as well as "Test Yourself"questions that help you gauge and reinforce your grasp of theinformation covered.
Author: Barry H. Cohen,R. Brooke Lea
Publisher: John Wiley & Sons