Statistical graphics for univariate and bivariate data / William G. Jacoby.

Format:

Book

Author/Creator:

Jacoby, William G.

Series:

Quantitative applications in the social sciences ; no. 07-117.

Sage university papers series. Quantitative applications in the social sciences ; 117

Language:

English

Subjects (All):

Statistics--Graphic methods.

Statistics.

Physical Description:

97 pages : illustrations ; 22 cm.

Place of Publication:

Thousand Oaks, Calif. : Sage Publications, [1997]

Summary:

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.

Contents:

What This Monograph Is (and is not) About 2

The Objectives of Graphical Methods 2

The Advantages of Graphical Approaches to Data Analysis 4

Graphical Perception 8

Detection 8

Assembly 9

Estimation 9

2. Graphical Displays for Univariate Data 13

Histograms 13

Smoothed Histograms 18

Unidimensional Scatterplots 30

Quantile Plots 32

Box Plots 38

Dot Plots 43

3. Graphical Displays for Bivariate Data 51

Definition and Construction Guidelines for Bivariate Scatterplots 52

Enhancements for Bivariate Scatterplots 54

Jittering for Overplotting and Repeated Data Points 54

Marginal Box Plots 56

Labeling Points 59

Slicing a Scatterplot 60

Nonparametric Scatterplot Smoothing 64

The Loess Smoother 64

The Details of Fitting a Loess Smooth Curve 66

Fitting Parameters and Diagnostics for the Loess Smooth Curve 72

Specifying [alpha], the Smoothing Parameter 72

Specifying [lambda], the Degree of Loess Polynomial 77

Goodness of Fit for a Loess Smooth Curve 83

Aspect Ratio and Banking to 45 Degrees 85.

Notes:

Includes bibliographical references (pages 89-96).

ISBN:

0761900837

OCLC:

35860947