
- 107 pages
- English
- PDF
- Available on iOS & Android
Statistical Graphics for Univariate and Bivariate Data
About this book
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.
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Information
Table of contents
- Cover
- Contents
- Series Editor’s Introduction
- Chapter 1 - Introduction
- What This Monograph Is (and is not) About
- The Objectives of Graphical Methods
- The Advantages of Graphical Approaches to Data Analysis
- Graphical Perception
- Detection
- Assembly
- Estimation
- Conclusions
- Chapter 2 - Graphical Displays for Univariate Data
- Histograms
- Smoothed Histograms
- Unidimensional Scatterplots
- Quantile Plots
- Box Plots
- Dot Plots
- Conclusions
- Chapter 3 - Graphical Displays for Bivariate Data
- Definition and Construction Guidelines for Bivariate Scatterplots
- Enhancements for Bivariate Scatterplots
- Jittering for Overplotting and Repeated Data Points
- Marginal Box Plots
- Labeling Points
- Slicing a Scatterplot
- Nonparametric Scatterplot Smoothing
- The Loess Smoother
- The Details of Fitting a Loess Smooth Curve
- Fitting Parameters and Diagnostics for the Loess Smooth Curve
- Specifying α, the Smoothing Parameter
- Specifying λ, the Degree of the Loess Polynomial
- Goodness of Fit for a Loess Smooth Curve
- Aspect Ratio and Banking to 45 Degrees
- Conclusions
- Chapter 4 - Conclusions
- Notes
- References
- About the Author