Statistical Methods For The Social Sciences
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Author | : Alan Agresti |
Publisher | : |
Total Pages | : 576 |
Release | : 2013-07-30 |
Genre | : Business & Economics |
ISBN | : 9781292021669 |
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.
Author | : Russell T. Warne |
Publisher | : Cambridge University Press |
Total Pages | : 612 |
Release | : 2020-12-17 |
Genre | : Psychology |
ISBN | : 110889853X |
The second edition of Statistics for the Social Sciences prepares students from a wide range of disciplines to interpret and learn the statistical methods critical to their field of study. By using the General Linear Model (GLM), the author builds a foundation that enables students to see how statistical methods are interrelated enabling them to build on the basic skills. The author makes statistics relevant to students' varying majors by using fascinating real-life examples from the social sciences. Students who use this edition will benefit from clear explanations, warnings against common erroneous beliefs about statistics, and the latest developments in the philosophy, reporting, and practice of statistics in the social sciences. The textbook is packed with helpful pedagogical features including learning goals, guided practice, and reflection questions.
Author | : Keming Yang |
Publisher | : SAGE |
Total Pages | : 218 |
Release | : 2010-03-25 |
Genre | : Social Science |
ISBN | : 1446205592 |
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.
Author | : David B. Flora |
Publisher | : SAGE |
Total Pages | : 786 |
Release | : 2017-12-11 |
Genre | : Social Science |
ISBN | : 1526421925 |
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.
Author | : Soleman H. Abu-Bader |
Publisher | : Oxford University Press |
Total Pages | : 395 |
Release | : 2011-07-01 |
Genre | : Social Science |
ISBN | : 0190685352 |
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.
Author | : S P Mukherjee |
Publisher | : Springer |
Total Pages | : 158 |
Release | : 2018-10-05 |
Genre | : Social Science |
ISBN | : 9811321469 |
This book presents various recently developed and traditional statistical techniques, which are increasingly being applied in social science research. The social sciences cover diverse phenomena arising in society, the economy and the environment, some of which are too complex to allow concrete statements; some cannot be defined by direct observations or measurements; some are culture- (or region-) specific, while others are generic and common. Statistics, being a scientific method – as distinct from a ‘science’ related to any one type of phenomena – is used to make inductive inferences regarding various phenomena. The book addresses both qualitative and quantitative research (a combination of which is essential in social science research) and offers valuable supplementary reading at an advanced level for researchers.
Author | : Daniel Stockemer |
Publisher | : Springer |
Total Pages | : 185 |
Release | : 2018-11-19 |
Genre | : Social Science |
ISBN | : 3319991183 |
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.
Author | : Norman R. Kurtz |
Publisher | : Prentice Hall |
Total Pages | : 410 |
Release | : 1999 |
Genre | : Business & Economics |
ISBN | : |
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.
Author | : R. Mark Sirkin |
Publisher | : SAGE Publications, Incorporated |
Total Pages | : 0 |
Release | : 1999-05-14 |
Genre | : Social Science |
ISBN | : 9780761914181 |
Do your students lack confidence in handling quantitative work? Do they get confused about how to enter statistical data on SAS and SPSS programs? This Second Edition of Mark Sirkin's popular textbook is the solution for these dilemmas. The book progresses from concepts that require little computational work to the more demanding. It emphasizes utilization so that students appreciate the usefulness of statistics and shows how the interpretation of data is related to the methods by which data was obtained. The author includes coverage of the scientific method, levels of measurement and the interpretation of tables.
Author | : Sean Gailmard |
Publisher | : Cambridge University Press |
Total Pages | : 393 |
Release | : 2014-06-09 |
Genre | : Business & Economics |
ISBN | : 1107003148 |
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 will also gain the ability to create, read and critique statistical applications in their fields of interest.