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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.

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Genre: Mathematics
Author: Eric A Hanushek
Publisher: Academic Press
Release: 2013-10-22
File: 374 Pages
ISBN-13: 9780080918570

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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.

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Genre: Social Science
Author: Soleman H. Abu-Bader
Publisher: Oxford University Press
Release: 2011-06-01
File: 394 Pages
ISBN-13: 9780190615222

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Genre:
Author: Lillian Cohen
Publisher:
Release: 1954
File: 181 Pages
ISBN-13: OCLC:1060813970

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People are bombarded with statistical data every day, but not many have had training in how to interpret or analyze this information. Kurtz's accessible writing style provides a basic yet sophisticated introduction to understanding and analyzing statistical applications. The book gives careful attention to the flow of ideas and concepts so there is a stream of logic which flows throughout, adding to the book's readability. The book begins with a discussion of methods for describing the distribution of a variable. The introduction of probability avoids the traditional discussion of the basic laws of probability, providing instead an explanation which can be directly applied in the everyday use of statistical probability. The discussion of the book is focused primarily on the relationship of probability to outcomes. Sociologists, psychologists, social workers, political scientists, educators, as well as anyone who wants to analyze data.

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Genre: Social Science
Author: Norman R. Kurtz
Publisher: Pearson College Division
Release: 1999
File: 379 Pages
ISBN-13: NWU:35556027822329

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The fourth edition has an even stronger emphasis on concepts and applications, with greater attention to "real data" both in the examples and exercises. The mathematics is still downplayed, in particular probability, which is all too often a stumbling block for students. On the other hand, the text is not a cookbook. Reliance on an overly simplistic recipe-based approach to statistics is not the route to good statistical practice. Changes in the Fourth Edition: Since the first edition, the increase in computer power coupled with the continued improvement and accessibility of statistical software has had a major impact on the way social scientists analyze data. Because of this, this book does not cover the traditional shortcut hand-computational formulas and approximations. The presentation of computationally complex methods, such as regression, emphasizes interpretation of software output rather than the formulas for performing the analysis. Teh text contains numerous sample printouts, mainly in the style of SPSS and occasionaly SAS, both in chapter text and homework problems. This edition also has an appendix explaining how to apply SPSS and SAS to conduct the methods of each chapter and a website giving links to information about other software.

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Genre: Business & Economics
Author: Alan Agresti
Publisher:
Release: 2013-07-30
File: 576 Pages
ISBN-13: 1292021667

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Written specifically for graduate students and practitioners beginning social science research, Statistical Modeling and Inference for Social Science covers the essential statistical tools, models and theories that make up the social scientist's toolkit. Assuming no prior knowledge of statistics, this textbook introduces students to probability theory, statistical inference and statistical modeling, and emphasizes the connection between statistical procedures and social science theory. Sean Gailmard develops core statistical theory as a set of tools to model and assess relationships between variables - the primary aim of social scientists - and demonstrates the ways in which social scientists express and test substantive theoretical arguments in various models. Chapter exercises guide students in applying concepts to data, extending their grasp of core theoretical concepts. Students gain the ability to create, read and critique statistical applications in their fields of interest.

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Genre: Business & Economics
Author: Sean Gailmard
Publisher: Cambridge University Press
Release: 2014-06-09
File: 388 Pages
ISBN-13: 9781107003149

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When I undertook the first edition of this book my goal was to introduce statistical methods in a style that emphasized their concepts and their application to the social sciences rather than the mathematics and computational details behind them. This fourth edition has an even stronger emphasis on concepts and applications, with greater attention to "real data" both in the examples and exercises.

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Genre: Social sciences
Author: Alan Agresti
Publisher: Prentice Hall
Release: 2009
File: 609 Pages
ISBN-13: 013713150X

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At last—a social scientist's guide through the pitfalls ofmodern statistical computing Addressing the current deficiency in the literature onstatistical methods as they apply to the social and behavioralsciences, Numerical Issues in Statistical Computing for the SocialScientist seeks to provide readers with a unique practicalguidebook to the numerical methods underlying computerizedstatistical calculations specific to these fields. The authorsdemonstrate that knowledge of these numerical methods and how theyare used in statistical packages is essential for making accurateinferences. With the aid of key contributors from both the socialand behavioral sciences, the authors have assembled a rich set ofinterrelated chapters designed to guide empirical social scientiststhrough the potential minefield of modern statisticalcomputing. Uniquely accessible and abounding in modern-day tools, tricks,and advice, the text successfully bridges the gap between thecurrent level of social science methodology and the moresophisticated technical coverage usually associated with thestatistical field. Highlights include: A focus on problems occurring in maximum likelihoodestimation Integrated examples of statistical computing (using softwarepackages such as the SAS, Gauss, Splus, R, Stata, LIMDEP, SPSS,WinBUGS, and MATLAB®) A guide to choosing accurate statistical packages Discussions of a multitude of computationally intensivestatistical approaches such as ecological inference, Markov chainMonte Carlo, and spatial regression analysis Emphasis on specific numerical problems, statisticalprocedures, and their applications in the field Replications and re-analysis of published social scienceresearch, using innovative numerical methods Key numerical estimation issues along with the means ofavoiding common pitfalls A related Web site includes test data for use in demonstratingnumerical problems, code for applying the original methodsdescribed in the book, and an online bibliography of Web resourcesfor the statistical computation Designed as an independent research tool, a professionalreference, or a classroom supplement, the book presents awell-thought-out treatment of a complex and multifaceted field.

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Genre: Mathematics
Author: Micah Altman
Publisher: John Wiley & Sons
Release: 2004-02-15
File: 323 Pages
ISBN-13: 9780471475743

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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.

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Genre: Social Science
Author: R. Mark Sirkin
Publisher: SAGE
Release: 2006
File: 610 Pages
ISBN-13: 141290546X

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Helping first-time students establish a solid foundation in analysis, this ground-up Canadian text uses a conversational tone, a wealth of practice problems and exercises, and clear examples to teach the universal language of statistics. Fully up-to-date, the third edition has been rigorouslyrevised to ensure the precision and accuracy of all concepts, equations, problems, and solutions.

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Genre: Social sciences
Author: Michael Haan
Publisher:
Release: 2016-10-05
File: 496 Pages
ISBN-13: 0199020590

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