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Doing Quantitative Research In Education With Spss

Author: Daniel Muijs
Publisher: SAGE
ISBN: 9781446242346
Size: 16.45 MB
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This accessible and authoritative introduction is essential for education students and researchers needing to use quantitative methods for the first time. Using datasets from real-life educational research and avoiding the use of mathematical formulae, the author guides students through the essential techniques that they will need to know, explaining each procedure using the latest version of SPSS. The datasets can also be downloaded from the book's website, enabling students to practice the techniques for themselves. This revised and updated second edition now also includes more advanced methods such as log linear analysis, logistic regression, and canonical correlation. Written specifically for those with no prior experience of quantitative research, this book is ideal for education students and researchers in this field.

Quantitative Data Analysis In Education

Author: Paul Connolly
Publisher: Routledge
ISBN: 1134191847
Size: 51.70 MB
Format: PDF, ePub, Mobi
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This book provides a refreshing and user-friendly guide to quantitative data analysis in education for students and researchers. It assumes absolutely no prior knowledge of quantitative methods or statistics. Beginning with the very basics, it provides the reader with the knowledge and skills necessary to be able to undertake routine quantitative data analysis to a level expected of published research. Rather than focusing on teaching statistics through mathematical formulae, the book places an emphasis on using SPSS to gain a real feel for the data and an intuitive grasp of the main concepts and techniques involved. Drawing extensively upon up-to-date and relevant examples, the reader will be encouraged to think critically about quantitative research and its potential as well as its limitations in relation to education. Packed with helpful features, this book: provides illustrated step-by-step guides showing how to use SPSS, with plenty of exercises to encourage the reader to practice and consolidate their new skills makes extensive use of real-life educational datasets derived from national surveys in the US and UK to illustrate key points and to bring the material to life has a companion website that contains all of the educational datasets used in the book to download as well as comprehensive answers to exercises and a range of other useful resources that are regularly updated. The book will therefore appeal not only to undergraduate and postgraduate students but also to more established and seasoned educational researchers and lecturers and professors who have tended to avoid or shy away from quantitative methods.

Quantitative Social Research Methods

Author: Kultar Singh
Publisher: SAGE Publishing India
ISBN: 9351500063
Size: 60.50 MB
Format: PDF
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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.

Understanding Educational Statistics Using Microsoft Excel And Spss

Author: Martin Lee Abbott
Publisher: John Wiley & Sons
ISBN: 1118627180
Size: 58.50 MB
Format: PDF, Docs
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Utilizing the latest software, this book presents the essential statistical procedures for drawing valuable results from data in the social sciences. Mobilizing interesting real-world examples from the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS supplies a seamless presentation that identifies valuable connections between statistical applications and research design. Class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations and the use of software packages that are accessible to both the novice and professional alike to present the fundamental statistical practices for organizing, understanding, and drawing conclusions from educational research data. The book begines with an introduction to descriptive and inferential statistics and then proceeds to acquaint readers with the various functions for working with quantitative data in the Microsoft Excel environment, such as spreadsheet navigation; sorting and filtering; and creating pivot tables. Subsequent chapters treat the procedures that are commonly-employed when working with data across various fields of social science research, including: Single-sample tests Repeated measure tests Independent t-tests One way ANOVA and factorial ANOVA Correlation Bivariate regression Chi square Multiple regression Individual chapters are devoted to specific procedures, each ending with a lab exercise that highlights the importance of that procedure by posing a research question, examining the question through its application in Excel and SPSS, and concluding with a brief research report that outlines key findings drawn from the results. Real-world examples and data from modern educational research are used throughout the book, and a related Web site features additional data sets, examples, and labs, allowing readers to reinforce their comprehension of the material. Bridging traditional statistical topics with the latest software and applications in the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS is an excellent book for courses on educational research methods and introductory statistics in the social sciences at the upper-undergraduate and graduate levels. It also serves as a valuable resource for researchers and practitioners in the fields of education, psychology, and the social sciences who require a statistical background to work with data in their everyday work.

Quantitative Data Analysis

Author: Donald J. Treiman
Publisher: John Wiley & Sons
ISBN: 0470380039
Size: 25.10 MB
Format: PDF
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"Quantitative Data Analysis, by Donald J. Treiman, is a well-written demonstration of how to answer questions using statistics. The range of techniques is broad, ranging from simple advice for making tables readily readable through linear and logistic regression to log-linear and random-effects models ... Treiman writes using clear, precise language ... Treiman also takes the time and effort to explain how to avoid common pitfalls of data analysis ... worth a look for those wanting to see the applications of a wide variety of statistical techniques to a variety of problems or for those who are inte.

The Reviewer S Guide To Quantitative Methods In The Social Sciences

Author: Gregory R. Hancock
Publisher: Routledge
ISBN: 1135172994
Size: 37.43 MB
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The Reviewer’s Guide is designed for reviewers of research manuscripts and proposals in the social and behavioral sciences, and beyond. Its uniquely structured chapters address traditional and emerging quantitative methods of data analysis.

Adventures In Social Research

Author: Earl Babbie
Publisher: SAGE Publications
ISBN: 148335959X
Size: 16.82 MB
Format: PDF, ePub
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Written by esteemed social science research authors Earl R. Babbie, William E. Wagner, and Jeanne Zaino, Adventures in Social Research: Data Analysis Using IBM® SPSS® Statistics, Ninth Edition encourages students to practice SPSS as they read about it, providing a practical, hands-on introduction to conceptualization, measurement, and association through active learning. This fully revised workbook will guide students through step-by-step instruction on data analysis using the latest version of SPSS and the most up to date General Social Survey data. Arranged to parallel most introductory research methods texts, this text starts with an introduction to computerized data analysis and the social research process, then takes readers step-by-step through univariate, bivariate, and multivariate analysis using SPSS Statistics. In this revised edition, active and collaborative learning will be emphasized as students engage in a series of practical investigative exercises.

An Intermediate Guide To Spss Programming

Author: Sarah Boslaugh
Publisher: SAGE
ISBN: 9780761931850
Size: 16.49 MB
Format: PDF
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An Intermediate Guide to SPSS Programming: Using Syntax for Data Management introduces the major tasks of data management and presents solutions using SPSS syntax. This book fills an important gap in the education of many students and researchers, whose coursework has left them unprepared for the data management issues that confront them when they begin to do independent research. It also serves as an introduction to SPSS programming. All the basic features of SPSS syntax are illustrated, as are many intermediate and advanced topics such as using vectors and loops, reading complex data files, and using the SPSS macro language.

Applied Multivariate Statistics For The Social Sciences

Author: Keenan A. Pituch
Publisher: Routledge
ISBN: 1317805925
Size: 67.64 MB
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Now in its 6th edition, the authoritative textbook Applied Multivariate Statistics for the Social Sciences, continues to provide advanced students with a practical and conceptual understanding of statistical procedures through examples and data-sets from actual research studies. With the added expertise of co-author Keenan Pituch (University of Texas-Austin), this 6th edition retains many key features of the previous editions, including its breadth and depth of coverage, a review chapter on matrix algebra, applied coverage of MANOVA, and emphasis on statistical power. In this new edition, the authors continue to provide practical guidelines for checking the data, assessing assumptions, interpreting, and reporting the results to help students analyze data from their own research confidently and professionally. Features new to this edition include: NEW chapter on Logistic Regression (Ch. 11) that helps readers understand and use this very flexible and widely used procedure NEW chapter on Multivariate Multilevel Modeling (Ch. 14) that helps readers understand the benefits of this "newer" procedure and how it can be used in conventional and multilevel settings NEW Example Results Section write-ups that illustrate how results should be presented in research papers and journal articles NEW coverage of missing data (Ch. 1) to help students understand and address problems associated with incomplete data Completely re-written chapters on Exploratory Factor Analysis (Ch. 9), Hierarchical Linear Modeling (Ch. 13), and Structural Equation Modeling (Ch. 16) with increased focus on understanding models and interpreting results NEW analysis summaries, inclusion of more syntax explanations, and reduction in the number of SPSS/SAS dialogue boxes to guide students through data analysis in a more streamlined and direct approach Updated syntax to reflect newest versions of IBM SPSS (21) /SAS (9.3) A free online resources site at www.routledge.com/9780415836661 with data sets and syntax from the text, additional data sets, and instructor’s resources (including PowerPoint lecture slides for select chapters, a conversion guide for 5th edition adopters, and answers to exercises). Ideal for advanced graduate-level courses in education, psychology, and other social sciences in which multivariate statistics, advanced statistics, or quantitative techniques courses are taught, this book also appeals to practicing researchers as a valuable reference. Pre-requisites include a course on factorial ANOVA and covariance; however, a working knowledge of matrix algebra is not assumed.