
Quantitative Research Methods in the Social Sciences
MAXIM(Author)
Oxford University Press Inc
Published in March 1999
Book
Hardback
416 pages
978-0-19-511465-2 (ISBN)
Description
A strong understanding and appreciation of statistics and quantitative research methods is vital to any graduate student of the social sciences. Yet the texts on these subjects that are written at a level appropriate for graduate students are few and far between. With this in mind, the author has designed a text suitable for first year graduate survey courses that reviews general statistical theory and method and explores the problems that quantitative social scientists face in conducting research. After providing an overview of the philosophical basis of neo-positivistic, quantitative social science, the book will present the concepts of theory formalization and casuality. It will then move into more specific areas, focusing extensively on issues of design and data collection. These issues will include experimental designs, mesasurement theory, classical test theory, data collection methods and measurement errors, micro simulation, sampling designs, and computer intensive techniques.
Reviews / Votes
"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 UniversityMore details
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Illustrations
tab., fig.
figures, tables
Dimensions
Height: 234 mm
Width: 156 mm
Weight
658 gr
ISBN-13
978-0-19-511465-2 (9780195114652)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Content
1: The Scientific Method 2: Theory Formalization 3: Causality 4: Statistical Inference 5: Sampling-Basic Concepts 6: Sampling-Designs 7: Sampling-Special Problems 8: Experimental Design 9: Measurement Theory 10: Classical Test Theory 11: Confirmatory Factor Models and Latent Variables 12: Data Collection and Measurement Errors 13: Missing Data 14: Interpolating and Smoothing 15: Computer Intensive Techniques -- Monte Carlo Procedures and Bootstrapping Bibliography/References Index