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Search Results for: statistical-methods-for-the-social-sciences

## Statistical Methods for the Social Sciences, Global Edition

For courses in Statistical Methods for the Social Sciences. Statistical methods applied to social sciences, made accessible to all through an emphasis on concepts Statistical Methods for the Social Sciences introduces statistical methods to students majoring in social science disciplines. With an emphasis on concepts and applications, this book assumes no previous knowledge of statistics and only a minimal mathematical background. It contains sufficient material for a two-semester course. The 5th Edition uses examples and exercises with a variety of "real data." It includes more illustrations of statistical software for computations and takes advantage of the outstanding applets to explain key concepts, such as sampling distributions and conducting basic data analyses. It continues to downplay mathematics--often a stumbling block for students--while avoiding reliance on an overly simplistic recipe-based approach to statistics.
## Statistical Methods for the Social and Behavioural Sciences

Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.
## New Statistical Procedures for the Social Sciences

This unique volume addresses the inadequacies of basic statistical methods that standard textbooks tend to ignore. The author introduces new procedures with accompanying tables that illustrate the practicality of the methods. Concentrating on basic experimental designs that are central to research in the social sciences, Wilcox describes new nonparametric techniques, two-way ANOVA designs, and new results related to the analysis of covariance and repeated measure design. This book serves as the ideal reference and supplement to standard texts by making the statistical advances of the last thirty years accessible to graduate students and researchers.
## Applied Statistical Methods

[NOTE: Is this the current title?] This book describes and explains the entire process of designing and building a distributed object application with the VisualAge Smalltalk Distributed feature.This book contains an overview of the features and architecture of SmallTalk's Distributed feature; sample application components with supporting documentation to illustrate design and coding; and recommendations for building distributed object applications with VisualAge. Learn how to set up the development environment, and special considerations for testing, run-time configurations, optimization and performance tuning.For software development managers, designers and others planning to develop client/server and peer-to-peer applications with distributed objects using VisualAge.
## Statistics for the Social Sciences

This introductory undergraduate textbook is the first statistics textbook built around the General Linear Model.
## Statistics for the Social Sciences

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.
## Statistical Methods for Social Scientists

The aspects of this text which we believe are novel, at least in degree, include: an effort to motivate different sections with practical examples and an empirical orientation; an effort to intersperse several easily motivated examples throughout the book and to maintain some continuity in these examples; and the extensive use of Monte Carlo simulations to demonstrate particular aspects of the problems and estimators being considered. In terms of material being presented, the unique aspects include the first chapter which attempts to address the use of empirical methods in the social sciences, the seventh chapter which considers models with discrete dependent variables and unobserved variables. Clearly these last two topics in particular are quite advanced--more advanced than material that is currently available on the subject. These last two topics are also currently experiencing rapid development and are not adequately described in most other texts.
## Student Solutions Manual for Statistical Methods for the Social Sciences

## Making Sense of Statistical Methods in Social Research

Making Sense of Statistical Methods in Social Research is a critical introduction to the use of statistical methods in social research. It provides a unique approach to statistics that concentrates on helping social researchers think about the conceptual basis for the statistical methods they're using. Whereas other statistical methods books instruct students in how to get through the statistics-based elements of their chosen course with as little mathematical knowledge as possible, this book aims to improve students' statistical literacy, with the ultimate goal of turning them into competent researchers. Making Sense of Statistical Methods in Social Research contains careful discussion of the conceptual foundation of statistical methods, specifying what questions they can, or cannot, answer. The logic of each statistical method or procedure is explained, drawing on the historical development of the method, existing publications that apply the method, and methodological discussions. Statistical techniques and procedures are presented not for the purpose of showing how to produce statistics with certain software packages, but as a way of illuminating the underlying logic behind the symbols. The limited statistical knowledge that students gain from straight forward 'how-to' books makes it very hard for students to move beyond introductory statistics courses to postgraduate study and research. This book should help to bridge this gap.
## Applied Multivariate Statistics for the Social Sciences

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.
## Relative Distribution Methods in the Social Sciences

This monograph presents methods for full comparative distributional analysis based on the relative distribution. This provides a general integrated framework for analysis, a graphical component that simplifies exploratory data analysis and display, a statistically valid basis for the development of hypothesis-driven summary measures, and the potential for decomposition - enabling the examination of complex hypotheses regarding the origins of distributional changes within and between groups. Written for data analysts and those interested in measurement, the text can also serve as a textbook for a course on distributional methods.
## Theory-Based Data Analysis for the Social Sciences

This book presents a method for bringing data analysis and statistical technique into line with theory. The author begins by describing the elaboration model for analyzing the empirical association between variables. She then introduces a new concept into this model, the focal relationship. Building upon the focal relationship as the cornerstone for all subsequent analysis, two analytic strategies are developed to establish its internal validity: an exclusionary strategy to eliminate alternative explanations, and an inclusive strategy which looks at the interconnected set of relationships predicted by theory. Using real examples of social research, the author demonstrates the use of this approach for two common forms of analysis, multiple linear regression and logistic regression. Whether learning data analysis for the first time or adding new techniques to your repertoire, this book provides an excellent basis for theory-based data analysis.
## Applied Multivariate Statistics for the Social Sciences

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.
## 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 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
## Applied Statistics Using Stata

Clear, intuitive and written with the social science student in mind, this book represents the ideal combination of statistical theory and practice. It focuses on questions that can be answered using statistics and addresses common themes and problems in a straightforward, easy-to-follow manner. The book carefully combines the conceptual aspects of statistics with detailed technical advice providing both the ‘why’ of statistics and the ‘how’. Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs. The book also provides: Original case studies and data sets Practical guidance on how to run and test models in Stata Downloadable Stata programmes created to work alongside chapters A wide range of detailed applications using Stata Step-by-step notes on writing the relevant code. This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.
## Quantitative Methods for the Social Sciences

This textbook offers an essential introduction to survey research and quantitative methods. Building on the premise that statistical methods need to be learned in a practical fashion, the book guides students through the various steps of the survey research process and helps to apply those steps toward a real example. In detail, the textbook introduces students to the four pillars of survey research and quantitative analysis: (1) the importance of survey research, (2) preparing a survey, (3) conducting a survey and (4) analyzing a survey. Students are shown how to create their own questionnaire based on some theoretically derived hypotheses to achieve empirical findings for a solid dataset. Lastly, they use said data to test their hypotheses in a bivariate and multivariate realm. The book explains the theory, rationale and mathematical foundations of these tests. In addition, it provides clear instructions on how to conduct the tests in SPSS and Stata. Given the breadth of its coverage, the textbook is suitable for introductory statistics, survey research or quantitative methods classes in the social sciences.
## Student's Solutions Manual for Statistical Methods for the Social Sciences

This manual contains completely worked-out solutions for all the odd-numbered exercises in the text.
## Dictionary of Statistics & Methodology

Written in a clear, readable style with a wide range of explanations and examples, the Fourth Edition of this must-have reference guide has been updated throughout to reflect recent changes in the fields of statistics and methodology. Packed with new terms, synonyms, and graphics, this best-selling dictionary provides readers with everything they need to read and understand a research report, including elementary terms and concepts and methodology and design definitions, as well as concepts from qualitative research methods and terms from theory and philosophy.
## Bayesian Statistics for the Social Sciences

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.
## Social science in the courtroom

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Author: Alan Agresti,Barbara Finlay

Publisher: N.A

ISBN: 9781292220314

Category:

Page: 568

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*A Model-Based Approach*

Author: David B. Flora

Publisher: SAGE

ISBN: 1526421925

Category: Social Science

Page: 472

View: 768

*Modern Solutions To Basic Problems*

Author: Rand R. Wilcox

Publisher: Psychology Press

ISBN: 1135059764

Category: Psychology

Page: 442

View: 4201

*For Business, Economics, and the Social Sciences*

Author: William Lee Carlson

Publisher: N.A

ISBN: 9780135708477

Category: Mathematics

Page: 1021

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Author: Russell T. Warne

Publisher: Cambridge University Press

ISBN: 1107576970

Category: Mathematics

Page: 601

View: 9074

Author: R. Mark Sirkin

Publisher: SAGE

ISBN: 9781412905466

Category: Mathematics

Page: 610

View: 379

Author: Eric A Hanushek,John E. Jackson

Publisher: Academic Press

ISBN: 0080918573

Category: Mathematics

Page: 374

View: 2371

Author: Alan Agresti,Barbara Finlay

Publisher: Pearson

ISBN: 9780136028130

Category: Business & Economics

Page: 76

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Author: Keming Yang

Publisher: SAGE

ISBN: 1446243869

Category: Social Science

Page: 216

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Author: James Paul Stevens

Publisher: Taylor & Francis

ISBN: 0805859012

Category: Social Science

Page: 651

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Author: Mark S. Handcock,Martina Morris

Publisher: Springer Science & Business Media

ISBN: 0387226583

Category: Social Science

Page: 266

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Author: Carol S. Aneshensel

Publisher: SAGE

ISBN: 1412994357

Category: Social Science

Page: 446

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*Analyses with SAS and IBM’s SPSS, Sixth Edition*

Author: Keenan A. Pituch,James P. Stevens

Publisher: Routledge

ISBN: 1317805917

Category: Psychology

Page: 814

View: 6886

Author: Soleman H. Abu-Bader

Publisher: N.A

ISBN: 9780190616397

Category:

Page: 350

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*A Guide for the Social Sciences*

Author: Mehmet Mehmetoglu,Tor Georg Jakobsen

Publisher: SAGE

ISBN: 1473987148

Category: Social Science

Page: 376

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*A Practical Introduction with Examples in SPSS and Stata*

Author: Daniel Stockemer

Publisher: Springer

ISBN: 3319991183

Category: Social Science

Page: 181

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Author: Alan Agresti

Publisher: Pearson

ISBN: 9780134512792

Category:

Page: 80

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*A Nontechnical Guide for the Social Sciences*

Author: W. Paul Vogt,R. Burke Johnson

Publisher: SAGE

ISBN: 1412971098

Category: Reference

Page: 437

View: 5063

Author: David Kaplan

Publisher: Guilford Publications

ISBN: 1462516513

Category: Psychology

Page: 318

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*statistical techniques and research methods for winning class-action suits*

Author: James W. Loewen

Publisher: Free Press

ISBN: N.A

Category: Law

Page: 234

View: 4817