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Statistical Graphics for Univariate and Bivariate Data
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Statistical Graphics for Univariate and Bivariate Data

  • William G. Jacoby - Michigan State University, USA, University of South Carolina, Colombia


104 pages | SAGE Publications, Inc
Graphical displays that researchers can employ as an integral part of the data analysis process are frequently more revealing than traditional, numerical summary statistics. Providing strategies for examining data more effectively, this volume focuses on: univariate methods such as histograms, smoothed histograms, univariate scatterplots, quantile plots, box plots, dot plots; and bivariate methods such as scatterplot construction guidelines, jittering for overplotted points, marginal boxplots, scatterplot slicing, the loess procedure for nonparametric scatterplot smoothing, banking to 45 degrees for enhanced visual perception.
 
Introduction
 
Graphical Displays for Univariate Data
 
Graphical Displays for Bivariate Data
 
Conclusions

William G. Jacoby

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... More About Author

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