Quantitative Research Methods in the Social Sciences by Paul S. MaximQuantitative Research Methods in the Social Sciences by Paul S. Maxim

Quantitative Research Methods in the Social Sciences

byPaul S. Maxim

Hardcover | January 1, 1999

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A strong understanding and appreciation of statistics and quantitative research methods is vital to any graduate student of the social sciences, yet most similar texts do not adequately cover this subject. With this in mind, the author has designed a text suitable for first-year graduatesurvey courses that reviews general statistical theory and methods and explores the problems that quantitative social scientists face in conducting research. The topics covered in this book range from the philosophical basis of scientific research to issues of statistical inference, measurement,scaling, research design, sampling, and problems with missing data. Numerous examples are drawn from a range of specialties to illustrate a variety of practical applications. After providing an overview of the philosophical basis of quantitative social science, the book presents the concepts oftheory formalization and causality. It then moves into more specific areas, focusing extensively on issues of design and data collection. Quantitative Research Methods in the Social Sciences is accessible to students with an intermediate-level background in social statistics and research methods.Professionals will find this detailed yet concise book to be an excellent reference. With over 350 classical and up-to-date citations, Quantitative Research Methods in the Social Sciences has something to offer all social science researchers.
Paul S. Maxim is at University of Western Ontario.
Title:Quantitative Research Methods in the Social SciencesFormat:HardcoverDimensions:416 pages, 6.1 × 9.21 × 0.98 inPublished:January 1, 1999Publisher:Oxford University Press

The following ISBNs are associated with this title:

ISBN - 10:0195114655

ISBN - 13:9780195114652

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Table of Contents

1. The Scientific Method2. Theory Formalization3. Causality4. Statistical Inference5. Sampling-Basic Concepts6. Sampling-Designs7. Sampling-Special Problems8. Experimental Design9. Measurement Theory10. Classical Test Theory11. Confirmatory Factor Models and Latent Variables12. Data Collection and Measurement Errors13. Missing Data14. Interpolating and Smoothing15. Computer Intensive Techniques -- Monte Carlo Procedures and BootstrappingBibliography/ReferencesIndex

Editorial Reviews

"Overall, this will be one of the finest comprehensive graduate-level texts on quantitative research methods to be published in the last couple of decades." --Kenneth Land, Duke University