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Author : John Fox
Publisher : SAGE
Page : 185 pages
File Size : 47,6 Mb
Release : 2009
Category : Social Science
ISBN : 9781412960809
The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods
Author : John Fox
Publisher : Unknown
Page : 0 pages
File Size : 42,9 Mb
Release : 2021
Category : Social sciences
ISBN : 1071878832
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression.
Author : John Fox
Publisher : SAGE Publications
Page : 199 pages
File Size : 46,6 Mb
Release : 2021-01-11
Category : Social Science
ISBN : 9781071833247
A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based and Bayesian methods. The volume concludes by applying mathematical concepts and operations to a familiar case, linear least-squares regression. The Second Edition pays more attention to visualization, including the elliptical geometry of quadratic forms and its application to statistics. It also covers some new topics, such as an introduction to Markov-Chain Monte Carlo methods, which are important in modern Bayesian statistics. A companion website includes materials that enable readers to use the R statistical computing environment to reproduce and explore computations and visualizations presented in the text. The book is an excellent companion to a "math camp" or a course designed to provide foundational mathematics needed to understand relatively advanced statistical methods.
Author : John Fox
Publisher : SAGE Publications
Page : 612 pages
File Size : 55,6 Mb
Release : 2015-03-18
Category : Social Science
ISBN : 9781483321318
Combining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes new chapters on mixed-effects models for hierarchical and longitudinal data. Although the text is largely accessible to readers with a modest background in statistics and mathematics, author John Fox also presents more advanced material in optional sections and chapters throughout the book. Accompanying website resources containing all answers to the end-of-chapter exercises. Answers to odd-numbered questions, as well as datasets and other student resources are available on the author′s website. NEW! Bonus chapter on Bayesian Estimation of Regression Models also available at the author′s website.
Author : Alwyn Scott
Publisher : Springer Science & Business Media
Page : 352 pages
File Size : 43,6 Mb
Release : 2007-12-14
Category : Science
ISBN : 9780387224633
This book will be of interest to anyone who wishes to know what role mathematics can play in attempting to comprehend the dynamics of the human brain. It also aims to serve as a general introduction to neuromathematics. The book gives the reader a qualitative understanding and working knowledge of useful mathematical applications to the field of neuroscience. The book is readable by those who have little knowledge of mathematics for neuroscience but are committed to begin acquiring such knowledge.
Author : David B. Flora
Publisher : SAGE
Page : 769 pages
File Size : 49,8 Mb
Release : 2017-12-11
Category : Social Science
ISBN : 9781526421920
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 : Sanford M. Dornbusch,Calvin Fisher Schmid
Publisher : New York, McGraw-Hill
Page : 274 pages
File Size : 47,9 Mb
Release : 1955
Category : Mathematics
ISBN : UOM:39015007183927
Author : Richard Startup,Elwyn T. Whittaker
Publisher : Routledge
Page : 0 pages
File Size : 54,5 Mb
Release : 2022
Category : Electronic
ISBN : 1032081562
Originally published in 1982, this book describes those basic ideas and techniques of statistics which should be known to every social scientist. The explanations are given in careful detail at a level of mathematical sophistication which will be readily attainable by students meeting statistical methods for the first time. All the methods described are applied to, and sometimes are motivated by, genuine problems of interest arising in sociology, social policy, politics or human geography. The authors often provide a meaningful discussion of the substantive problem itself in addition to an analysis of the statistical techniques being used on it. In this way subject matter and statistical techniques are integrated in an original and effective manner. The authors combine considerable experience of shared teaching of social statistics with familiarity with its use in practical fields and in research. Their book therefore focuses on the most directly applicable methods and is carefully sequenced to promote rapid student understanding. The topic of probability - which so often confuses students - is here dealt with simply yet thoroughly. The chapter on the sources of social statistics, whilst being unusual in a text of this kind, is particularly welcome and comprehensively meets the needs of students on a wide range of courses. Introducing Social Statistics will make the vitally important field of statistics accessible to all students of the social sciences.
Author : jimi adams
Publisher : SAGE Publications
Page : 180 pages
File Size : 51,7 Mb
Release : 2019-06-03
Category : Social Science
ISBN : 9781544321455
Gathering Social Network Data fills an important gap in the literature by focusing on methods for designing, collecting, and evaluating the data that are the subject of these analytic techniques. Author jimi adams draws on his extensive teaching experience to provide a guide that can be used by both novice and more experienced researchers alike. The volume focuses on principles, with the goal of providing readers the tools needed to develop their own approach to gathering social network data.
Author : George Engelhard, Jr.,Jue Wang
Publisher : SAGE Publications
Page : 102 pages
File Size : 52,6 Mb
Release : 2020-12-13
Category : Social Science
ISBN : 9781544363011
This book introduces current perspectives on Rasch measurement theory with an emphasis on developing Rasch-based scales. Rasch measurement theory represents a paradigm shift in measurement theory away from classical test theory and creates a framework for scaling that can yield invariant measurement. Rasch Models for Solving Measurement Problems: Invariant Measurement in the Social Sciences is a broadly accessible text. Authors George Engelhard Jr and Jue Wang introduce Rasch measurement theory step by step, with chapters on scale construction, evaluation, maintenance, and use. Points are illustrated and techniques are demonstrated through an extended example: The Food Insecurity Experience (FIE) Scale. The Rasch analyses in the book are run using the Facets computer program. Facets syntax, and R code for the ERMA program created by the authors to obtain parameter estimates and to examine model-data fit, together with sample data sets are all available on a website for the book.
Author : Haiyan Bai,M. H. Clark
Publisher : SAGE Publications
Page : 137 pages
File Size : 55,9 Mb
Release : 2018-11-20
Category : Social Science
ISBN : 9781506378060
A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method. Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.
Author : James Alan Fox
Publisher : SAGE Publications
Page : 145 pages
File Size : 52,5 Mb
Release : 2015-07-29
Category : Social Science
ISBN : 9781483381022
Randomized response is a data collection strategy specifically designed for surveys of a sensitive nature. By establishing a probabilistic connection between question and answer, randomized response and related methods protect respondents who are asked to disclose personal information. Covering a half century of theoretical and applied research, the Second Edition of James Alan Fox’s Randomized Response and Related Methods significantly updates and expands what was, at the time, the first comprehensive and practical guide to randomized response.
Author : John Levi Martin
Publisher : University of Chicago Press
Page : 377 pages
File Size : 49,7 Mb
Release : 2018-08-21
Category : Social Science
ISBN : 9780226567778
Simply put, Thinking Through Statistics is a primer on how to maintain rigorous data standards in social science work, and one that makes a strong case for revising the way that we try to use statistics to support our theories. But don’t let that daunt you. With clever examples and witty takeaways, John Levi Martin proves himself to be a most affable tour guide through these scholarly waters. Martin argues that the task of social statistics isn't to estimate parameters, but to reject false theory. He illustrates common pitfalls that can keep researchers from doing just that using a combination of visualizations, re-analyses, and simulations. Thinking Through Statistics gives social science practitioners accessible insight into troves of wisdom that would normally have to be earned through arduous trial and error, and it does so with a lighthearted approach that ensures this field guide is anything but stodgy.
Author : Bruno Castanho Silva,Constantin Manuel Bosancianu,Levente Littvay
Publisher : SAGE Publications
Page : 145 pages
File Size : 45,7 Mb
Release : 2019-02-28
Category : Social Science
ISBN : 9781544323060
Multilevel Structural Equation Modeling by Bruno Castanho Silva, Constantin Manuel Bosancianu, and Levente Littvay serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the social sciences. As the first book of its kind, this title is an accessible, hands-on introduction for beginners of the topic. The authors predict a growth in this area, fueled by both data availability and also the availability of new and improved software to run these models. The applied approach, combined with a graphical presentation style and minimal reliance on complex matrix algebra guarantee that this volume will be useful to social science graduate students wanting to utilize such models.
Author : Colin Lewis-Beck,Michael Lewis-Beck
Publisher : SAGE Publications
Page : 121 pages
File Size : 44,9 Mb
Release : 2015-06-18
Category : Social Science
ISBN : 9781483381466
Known for its readability and clarity, this Second Edition of the best-selling Applied Regression provides an accessible introduction to regression analysis for social scientists and other professionals who want to model quantitative data. After covering the basic idea of fitting a straight line to a scatter of data points, the text uses clear language to explain both the mathematics and assumptions behind the simple linear regression model. Authors Colin Lewis-Beck and Michael Lewis-Beck then cover more specialized subjects of regression analysis, such as multiple regression, measures of model fit, analysis of residuals, interaction effects, multicollinearity, and prediction. Throughout the text, graphical and applied examples help explain and demonstrate the power and broad applicability of regression analysis for answering scientific questions.
