Statistical Modelling For Social Researchers


Statistical Modelling For Social Researchers
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Statistical Modelling For Social Researchers


Statistical Modelling For Social Researchers
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Author : Roger Tarling
language : en
Publisher: Routledge
Release Date : 2008-09-16

Statistical Modelling For Social Researchers written by Roger Tarling and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-09-16 with Social Science categories.


This book explains the principles and theory of statistical modelling in an intelligible way for the non-mathematical social scientist looking to apply statistical modelling techniques in research. The book also serves as an introduction for those wishing to develop more detailed knowledge and skills in statistical modelling. Rather than present a limited number of statistical models in great depth, the aim is to provide a comprehensive overview of the statistical models currently adopted in social research, in order that the researcher can make appropriate choices and select the most suitable model for the research question to be addressed. To facilitate application, the book also offers practical guidance and instruction in fitting models using SPSS and Stata, the most popular statistical computer software which is available to most social researchers. Instruction in using MLwiN is also given. Models covered in the book include; multiple regression, binary, multinomial and ordered logistic regression, log-linear models, multilevel models, latent variable models (factor analysis), path analysis and simultaneous equation models and models for longitudinal data and event histories. An accompanying website hosts the datasets and further exercises in order that the reader may practice developing statistical models. An ideal tool for postgraduate social science students, research students and practicing social researchers in universities, market research, government social research and the voluntary sector.



Statistical Methods For The Social And Behavioural Sciences


Statistical Methods For The Social And Behavioural Sciences
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Author : David B. Flora
language : en
Publisher: SAGE
Release Date : 2017-12-11

Statistical Methods For The Social And Behavioural Sciences written by David B. Flora and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-11 with Social Science categories.


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.



Statistical Modeling And Inference For Social Science


Statistical Modeling And Inference For Social Science
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Author : Sean Gailmard
language : en
Publisher:
Release Date : 2014

Statistical Modeling And Inference For Social Science written by Sean Gailmard and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Social sciences categories.


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.



Handbook Of Computational Social Science Volume 2


Handbook Of Computational Social Science Volume 2
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Author : Uwe Engel
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-10

Handbook Of Computational Social Science Volume 2 written by Uwe Engel and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.


The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors.



Linear Statistical Models And Related Methods


Linear Statistical Models And Related Methods
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Author : John Fox
language : en
Publisher: New York ; Toronto : Wiley
Release Date : 1984

Linear Statistical Models And Related Methods written by John Fox and has been published by New York ; Toronto : Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Mathematics categories.




Statistical Modeling And Inference For Social Science


Statistical Modeling And Inference For Social Science
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Author : Sean Gailmard
language : en
Publisher: Cambridge University Press
Release Date : 2014-06-09

Statistical Modeling And Inference For Social Science written by Sean Gailmard and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-09 with Business & Economics categories.


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.



The Multivariate Social Scientist


The Multivariate Social Scientist
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Author : Graeme D Hutcheson
language : en
Publisher: SAGE
Release Date : 1999-05-19

The Multivariate Social Scientist written by Graeme D Hutcheson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-19 with Social Science categories.


Starting from simple hypothesis testing and then moving towards model-building, this valuable book takes readers through the basics of multivariate analysis including: which tests to use on which data; how to run analyses in SPSS for Windows and GLIM4; how to interpret results; and how to report and present the reports appropriately. Using a unified conceptual framework (based around the Generalized Linear Model) the authors explain the commonalities and relationships between methods that include both the analysis of categorical and continuous data.



Statistical Models And Causal Inference


Statistical Models And Causal Inference
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Author : David A. Freedman
language : en
Publisher: Cambridge University Press
Release Date : 2010

Statistical Models And Causal Inference written by David A. Freedman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Mathematics categories.


David A. Freedman presents a definitive synthesis of his approach to statistical modeling and causal inference in the social sciences.



Making Sense Of Statistical Methods In Social Research


Making Sense Of Statistical Methods In Social Research
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Author : Keming Yang
language : en
Publisher: SAGE
Release Date : 2010-03-25

Making Sense Of Statistical Methods In Social Research written by Keming Yang and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-25 with Social Science categories.


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.



Statistical Principles And Techniques In Scientific And Social Research


Statistical Principles And Techniques In Scientific And Social Research
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Author : Wojtek J. Krzanowski
language : en
Publisher: OUP Oxford
Release Date : 2007-06-07

Statistical Principles And Techniques In Scientific And Social Research written by Wojtek J. Krzanowski and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-07 with Mathematics categories.


This graduate-level text provides a survey of the logic and reasoning underpinning statistical analysis, as well as giving a broad-brush overview of the various statistical techniques that play a major role in scientific and social investigations. Arranged in rough historical order, the text starts with the ideas of probability that underpin statistical methods and progresses through the developments of the nineteenth and twentieth centuries to modern concerns and solutions. Assuming only a basic level of Mathematics and with numerous examples and illustrations, this text presents a valuable resource not only to the experienced researcher but also to the student, by complementing courses in a wide range of substantive areas and enabling the reader to rise above the details in order to see the overall structure of the subject.