Data Analysis And Statistical Methods For Social Science Research
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Statistical Methods In Social Science Research
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Author : S P Mukherjee
language : en
Publisher: Springer
Release Date : 2018-10-05
Statistical Methods In Social Science Research written by S P Mukherjee and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-05 with Social Science categories.
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.
Data Analytics For The Social Sciences
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Author : G. DAVID. GARSON
language : en
Publisher: Routledge
Release Date : 2021-11-30
Data Analytics For The Social Sciences written by G. DAVID. GARSON and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-30 with categories.
This book presents a complete exploration of statistical data analysis in R for a wide variety of social science disciplines and quantitative methods courses.
Data Analysis And Statistical Methods For Social Science Research
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Author : Pasquale De Marco
language : en
Publisher: Pasquale De Marco
Release Date : 2025-04-20
Data Analysis And Statistical Methods For Social Science Research written by Pasquale De Marco and has been published by Pasquale De Marco this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-20 with Social Science categories.
**Data Analysis and Statistical Methods for Social Science Research** provides a comprehensive introduction to the fundamental concepts and techniques of statistical analysis for social science researchers. With a focus on practical application and real-world examples, this book offers a step-by-step approach to conducting statistical analyses, covering a wide range of topics essential for social science research. From the basics of statistical data collection and visualization to advanced statistical techniques such as multivariate analysis and time series analysis, this book provides a thorough overview of the field. Key features of the book include clear and concise explanations of statistical concepts and techniques, extensive use of real-world examples and case studies to illustrate the practical application of statistical methods in social science research, and step-by-step guidance on conducting statistical analyses using popular statistical software packages. This book is an invaluable resource for social science researchers, students, and practitioners who seek to enhance their understanding of data analysis and statistical methods. With its comprehensive coverage of statistical topics and its focus on practical application, this book provides the necessary knowledge and skills to effectively analyze data and gain valuable insights from research findings. This book is also a valuable resource for professionals in fields such as healthcare, education, and business who need to analyze data to make informed decisions. By providing a clear and comprehensive understanding of statistical methods, this book empowers readers to confidently analyze data and extract meaningful insights to address real-world problems. **Key Features:** * Comprehensive coverage of statistical concepts and techniques * Extensive use of real-world examples and case studies * Step-by-step guidance on conducting statistical analyses * Clear and concise explanations of statistical concepts * Focus on practical application of statistical methods * Valuable resource for social science researchers, students, and practitioners If you like this book, write a review on google books!
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.
Quantitative Social Science
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Author : Kosuke Imai
language : en
Publisher: Princeton University Press
Release Date : 2021-03-16
Quantitative Social Science written by Kosuke Imai and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-16 with Political Science categories.
"Princeton University Press published Imai's textbook, Quantitative Social Science: An Introduction, an introduction to quantitative methods and data science for upper level undergrads and graduates in professional programs, in February 2017. What is distinct about the book is how it leads students through a series of applied examples of statistical methods, drawing on real examples from social science research. The original book was prepared with the statistical software R, which is freely available online and has gained in popularity in recent years. But many existing courses in statistics and data sciences, particularly in some subject areas like sociology and law, use STATA, another general purpose package that has been the market leader since the 1980s. We've had several requests for STATA versions of the text as many programs use it by default. This is a "translation" of the original text, keeping all the current pedagogical text but inserting the necessary code and outputs from STATA in their place"--
Theory Based Data Analysis For The Social Sciences
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Author : Carol S. Aneshensel
language : en
Publisher: SAGE
Release Date : 2013
Theory Based Data Analysis For The Social Sciences written by Carol S. Aneshensel and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Reference categories.
This book presents the elaboration model for the multivariate analysis of observational quantitative data. This model entails the systematic introduction of "third variables" to the analysis of a focal relationship between one independent and one dependent variable to ascertain whether an inference of causality is justified. Two complementary strategies are used: an exclusionary strategy that rules out alternative explanations such as spuriousness and redundancy with competing theories, and an inclusive strategy that connects the focal relationship to a network of other relationships, including the hypothesized causal mechanisms linking the focal independent variable to the focal dependent variable. The primary emphasis is on the translation of theory into a logical analytic strategy and the interpretation of results. The elaboration model is applied with case studies drawn from newly published research that serve as prototypes for aligning theory and the data analytic plan used to test it; these studies are drawn from a wide range of substantive topics in the social sciences, such as emotion management in the workplace, subjective age identification during the transition to adulthood, and the relationship between religious and paranormal beliefs. The second application of the elaboration model is in the form of original data analysis presented in two Analysis Journals that are integrated throughout the text and implement the full elaboration model. Using real data, not contrived examples, the text provides a step-by-step guide through the process of integrating theory with data analysis in order to arrive at meaningful answers to research questions.
Using R For Data Analysis In Social Sciences
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Author : Quan Li
language : en
Publisher: Oxford University Press
Release Date : 2018
Using R For Data Analysis In Social Sciences written by Quan Li and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how to use R to manage, visualize, and analyze data. The focus is on how to address substantive questions with data analysis and replicate published findings. Using R for Data Analysis in Social Sciences adopts a minimalist approach and covers only the most important functions and skills in R to conduct reproducible research. It emphasizes the practical needs of students using R by showing how to import, inspect, and manage data, understand the logic of statistical inference, visualize data and findings via histograms, boxplots, scatterplots, and diagnostic plots, and analyze data using one-sample t-test, difference-of-means test, covariance, correlation, ordinary least squares (OLS) regression, and model assumption diagnostics. It also demonstrates how to replicate the findings in published journal articles and diagnose model assumption violations. Because the book integrates R programming, the logic and steps of statistical inference, and the process of empirical social scientific research in a highly accessible and structured fashion, it is appropriate for any introductory course on R, data analysis, and empirical social-scientific research.
Quantitative Methods For The Social Sciences
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Author : Daniel Stockemer
language : en
Publisher: Springer
Release Date : 2018-11-19
Quantitative Methods For The Social Sciences written by Daniel Stockemer and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-19 with Social Science categories.
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.
Research Methods And Data Analysis For Business Decisions
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Author : James E. Sallis
language : en
Publisher: Springer Nature
Release Date : 2021-10-30
Research Methods And Data Analysis For Business Decisions written by James E. Sallis and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-30 with Business & Economics categories.
This introductory textbook presents research methods and data analysis tools in non-technical language. It explains the research process and the basics of qualitative and quantitative data analysis, including procedures and methods, analysis, interpretation, and applications using hands-on data examples in QDA Miner Lite and IBM SPSS Statistics software. The book is divided into four parts that address study and research design; data collection, qualitative methods and surveys; statistical methods, including hypothesis testing, regression, cluster and factor analysis; and reporting. The intended audience is business and social science students learning scientific research methods, however, given its business context, the book will be equally useful for decision-makers in businesses and organizations.
Social Science Research Design And Statistics
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Author : Alfred P. Rovai
language : en
Publisher:
Release Date : 2012-09-01
Social Science Research Design And Statistics written by Alfred P. Rovai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-09-01 with Computers categories.
This book integrates social science research methods and the descriptions of 46 univariate, bivariate, and multivariate tests to include a description of the purpose, assumptions, example research question and hypothesis, SPSS procedure, and interpretation of SPSS output for each test. Included throughout the book are various sidebars highlighting key points, images and SPSS screenshots to assist understanding the material presented, self-test reviews at the end of each chapter, a decision tree to facilitate identification of the proper statistical test, examples of SPSS output with accompanying analysis and interpretations, links to relevant web sites, and a comprehensive glossary. Underpinning all these features is a concise, easy to understand explanation of the material.