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Advanced Quantitative Data Analysis

Author: Cramer, Duncan
Publisher: McGraw-Hill Education (UK)
ISBN: 0335200591
Size: 46.95 MB
Format: PDF, ePub
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There are a variety of statistical techniques used to analyse quantitative data that masters students, advanced undergraduates and researchers in the social sciences are expected to be able to understand and undertake. This book explains these techniques, when it is appropriate to use them, how to carry them out and how to write up the results. The following features characterize this book: concise and accessible introduction to calculating and interpreting advanced statistical techniques; use of a small data set of simple numbers specifically designed to illustrate the nature and manual calculation of the most important statistics in each technique; succinct illustration of writing up the results of these analyses; minimum of mathematical, statistical and technical notation; annotated bibliography and glossary of key concepts.

Best Practices In Quantitative Methods

Author: Jason W. Osborne
Publisher: SAGE
ISBN: 1412940656
Size: 65.11 MB
Format: PDF, Docs
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The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.

Quantitative Methods In Social Work

Author: David F. Gillespie
Publisher: Psychology Press
ISBN: 9781560242741
Size: 45.81 MB
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Representing some of the best research efforts currently found among social workers, Quantitative Methods in Social Work serves as both a guide and a challenge to social work researchers interested in the application of quantitative methods to social work problem solving. This application of research methods has not been described or discussed adequately in any formal way until now. In a comprehensive manner, this book documents the most advanced quantitative methodologies currently applied by social work researchers and describes issues and techniques that accompany specific applications. It increases social workers'understanding of state-of-the-art applied statistical analysis, enabling them to become more competent and competitive in research and the teaching of research strategies. Quantitative Methods in Social Work addresses three types of methodological issues: measurement, the incorporation of nonquantitative variables in quantitative data analysis, and the use of quantitative analytic techniques to model and assess complex social phenomena. Chapters cover the use of computers for content analysis, structural equation modeling in measurement, logistic regression, loglinear analysis, event history analysis, social network analysis, and discussions of moderator variables and interaction effects in multiple regression. Social work faculty and doctoral students, along with other human service professionals who want to increase their understanding of applied statistical analysis in social and behavioral research, will find the information they need in this informative book.

Quantitative Data Analysis

Author: Donald J. Treiman
Publisher: John Wiley & Sons
ISBN: 111851260X
Size: 32.82 MB
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This book is an accessible introduction to quantitative data analysis, concentrating on the key issues facing those new to research, such as how to decide which statistical procedure is suitable, and how to interpret the subsequent results. Each chapter includes illustrative examples and a set of exercises that allows readers to test their understanding of the topic. The book, written for graduate students in the social sciences, public health, and education, offers a practical approach to making sociological sense out of a body of quantitative data. The book also will be useful to more experienced researchers who need a readily accessible handbook on quantitative methods. The author has posted stata files, updates and data sets at his website http://tinyurl.com/Treiman-stata-files-data-sets.

Quantitative Social Research Methods

Author: Kultar Singh
Publisher: SAGE
ISBN: 0761933832
Size: 40.24 MB
Format: PDF, ePub, Docs
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Quantitative Social Research Methods explores the entire spectrum of quantitative social research methods and their application, with special reference to the development sector. It provides detailed coverage of all statistical research and analysis method with an emphasis on multivariate analysis techniques, such as regression discriminant analysis, logistic regression, factor, factor, cluster, correspondence and conjoint analysis. The book is thematically arranged in two sections: the first section introduces development research techniques, explores the genesis and scope of social research, research processes and then goes on to explain univariate, bivariate and multivariate data analysis with the help of software packages such as SPSS and STATA. The second focuses on the application of social and development research methods in the development sector. It explores research method application and the issues relevant to aspects of development such as population, health and nutrition, poverty and rural development, education, water and sanitation, and environment and natural resource management.

Analyzing Quantitative Data

Author: Debra Wetcher-Hendricks
Publisher: John Wiley & Sons
ISBN: 1118626117
Size: 68.33 MB
Format: PDF, ePub
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A user-friendly, hands-on guide to recognizing and conducting proper research techniques in data collection Offering a unique approach to numerical research methods, Analyzing Quantitative Data: An Introduction for Social Researchers presents readers with the necessary statistical applications for carrying out the key phases of conducting and evaluating a research project. The book guides readers through the steps of data analysis, from organizing raw data to utilizing descriptive statistics and tests of significance, drawing valid conclusions, and writing research reports. The author successfully provides a presentation that is accessible and hands-on rather than heavily theoretical, outlining the key quantitative processes and the use of software to successfully draw valid conclusions from gathered data. In its discussion of methods for organizing data, the book includes suggestions for coding and entry into spreadsheets or databases while also introducing commonly used descriptive statistics and clarifying their roles in data analysis. Next, inferential statistics is explored in-depth with explanations of and instructions for performing chi-square tests, t-tests, analyses of variance, correlation and regression analyses, and a number of advanced statistical procedures. Each chapter contains explanations of when to use the tests described, relevant formulas, and sample computations. The book concludes with guidance on extracting meaningful conclusions from statistical tests and writing research reports that describe procedures and analyses. Throughout the book, Statistical Resources for SPSS® sections provide fundamental instruction for using SPSS® to obtain the results presented. Where necessary, the author provides basic theoretical explanations for distributions and background information regarding formulas. Each chapter concludes with practice problems, and a related website features derivations of the book's formulas along with additional resources for performing the discussed processes. Analyzing Quantitative Data is an excellent book for social sciences courses on data analysis and research methods at the upper-undergraduate and graduate levels. It also serves as a valuable reference for applied statisticians and practitioners working in the fields of education, medicine, business and public service who analyze, interpret, and evaluate data in their daily work.

What Is Quantitative Longitudinal Data Analysis

Author: Vernon Gayle
Publisher: Bloomsbury Publishing
ISBN: 1472515412
Size: 18.15 MB
Format: PDF, ePub, Mobi
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Across the social sciences, there is widespread agreement that quantitative longitudinal research designs offer analysts powerful scientific data resources. But, to date, many texts on analysing longitudinal social analysis surveys have been written from a statistical, rather than a social science data analysis perspective and they lack adequate coverage of common practical challenges associated with social science data analyses. This book provides a practical and up-to-date introduction to influential approaches to quantitative longitudinal data analysis in the social sciences. The book introduces definitions and terms, explains the relative attractions of such a longitudinal design, and offers an introduction to the main techniques of analysis, explaining their requirements, statistical properties and their substantive contribution. The book is designed for postgraduates and researchers across the social sciences considering the use of quantitative longitudinal data resources in their research. It will also be an excellent text for undergraduate and postgraduate courses on advanced quantitative methods.

Analyzing Quantitative Data

Author: Norman Blaikie
Publisher: SAGE
ISBN: 9780761967590
Size: 23.44 MB
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For social researchers who need to know what procedures to use under what circumstances in practical research projects, this book does not require an indepth understanding of statistical theory.

Social Theory And Applied Health Research

Author: Dyson, Simon
Publisher: McGraw-Hill Education (UK)
ISBN: 033522492X
Size: 40.54 MB
Format: PDF, Kindle
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Social Theory and Applied Health Research provides an accessible assessment of dilemmas facing social researchers in trying to make sense of the world of health care. It links theory and method by presenting an account of how reflection can help amend, complement and strengthen a practical research strategy. Using clear diagrams, tables and examples of recent research, the book illustrates principles from social theory from a range of applied research studies.

Handbook Of Ethics In Quantitative Methodology

Author: Sonya K. Sterba
Publisher: Taylor & Francis
ISBN: 113688873X
Size: 80.27 MB
Format: PDF, Mobi
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"Part 1 presents ethical frameworks that cross-cut design, analysis, and modeling in the behavioral sciences. Part 2 focuses on ideas for disseminating ethical training in statistics courses. Part 3 considers the ethical aspects of selecting measurement instruments and sample size planning and explores issues related to high stakes testing, the defensibility of experimental vs. quasi-experimental research designs, and ethics in program evaluation. Decision points that shape a researchers' approach to data analysis are examined in Part 4 - when and why analysts need to account for how the sample was selected, how to evaluate tradeoffs of hypothesis-testing vs. estimation, and how to handle missing data. Ethical issues that arise when using techniques such as factor analysis or multilevel modeling and when making causal inferences are also explored. The book concludes with ethical aspects of reporting meta-analyses, of cross-disciplinary statistical reform, and of the publication process.