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Statistical Graphics for Univariate and Bivariate Data
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Statistical Graphics for Univariate and Bivariate Data Paperback - 1997 - 1st Edition

by William G. Jacoby; Introduction by Michael S. Lewis-Beck

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From the publisher

Author William G. Jacoby focuses on graphical displays that researchers can employ as an integral part of the data analysis process. Such visual depictions are frequently more revealing than traditional, numerical summary statistics. Accessibly written, this book contains chapters on univariate and bivariate methods. The former covers histograms, smoothed histograms, univariate scatterplots, quantile plots, box plots, and dot plots. The latter covers scatterplot construction guidelines, jittering for overplotted points, marginal box plots, scatterplot slicing, the Loess procedure for nonparametric scatterplot smoothing, and banking to 45 degrees for enhanced visual perception. This book provides strategies for examining data more effectively. The resultant insights help researchers avoid the problem of forcing an inaccurate model onto uncooperative data and guide analysts to model specifications that provide accurate representations of empirical information.


Details

  • Title Statistical Graphics for Univariate and Bivariate Data
  • Author William G. Jacoby; Introduction by Michael S. Lewis-Beck
  • Binding Paperback
  • Edition number 1st
  • Edition 1
  • Pages 104
  • Volumes 1
  • Language ENG
  • Publisher Sage Publications, Inc.
  • Publication date 1997-02-24
  • Illustrated Yes
  • Features Bibliography, Illustrated, Table of Contents
  • ISBN 9780761900832 / 0761900837
  • Weight 0.3 lbs (0.14 kg)
  • Dimensions 8.06 x 6 x 0.26 in (20.47 x 15.24 x 0.66 cm)
  • Category Medical / Nursing
  • Library of Congress subjects Statistics - Graphic methods
  • Library of Congress Catalogue Number 96045892
  • Dewey Decimal Code 001.422

About the author

William G. Jacoby is a Professor in the Department of Political Science at Michigan State University. He is also a Research Scientist at the University of Michigan, where he serves as Director of the Inter-University Consortium for Political and Social Research (ICPSR) Summer Training Program in Quantitative Methods of Social Research.
Professor Jacoby joined the MSU faculty in 2003. Previously, he held positions at the University of South Carolina, Ohio State University, and the University of Missouri. He received his Ph.D. from the University of North Carolina, Chapel Hill in 1983.
Professor Jacoby′s main professional interests are mass political behavior (public opinion, political attitudes, voting behavior) and quantitative methodology (measurement theory, scaling methods, statistical graphics, modern regression). His current research focuses on citizen ideology and belief system organization, value choices and their implications for subsequent political orientations, measuring policy priorities in the American states, the implications of measurement assumptions for statistical models, and graphical strategies for data analysis.
Recently, Professor Jacoby has taught courses on public opinion, regression analysis, scaling methods, and statistical graphics.

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Statistical Graphics for Univariate and Bivariate Data

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Statistical Graphics for Univariate and Bivariate Data (Quantitative Applications in the Social Sciences)

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