Students are instructed on how to create the most common graphs in public administration research and data visualization.Correct data setup for each graph is illustrated through the use of datasets in the Companion Site.Graphs include bar graphs, histograms, line graphs, boxplots, and scatterplots.Steps to produce these graphs in R Commander are covered using public administration examples and datasets.

Chapter 2 covers univariate distributions and includes the following specific topics, among others: Frequency and Percent Distribution Tables, Bar Charts, Pie Charts, Stem-and-Leaf Displays, Histograms, Line Graphs, Shape of a Distribution, Cumulative Percent Distributions, Percentiles, Percentile Ranks, and Boxplots.

Chapter 2 covers univariate distributions and includes the following specific topics, among others: frequency and percent distribution tables, bar charts, pie charts, stem-and-leaf displays, histograms, line graphs, shape of a distribution, cumulative percent. Distributions, Percentiles, Percentile Ranks, and Boxplots.

This chapter gives examples of very basic graphs and charts and how to read them. Such graphs and charts are used by clinicians and by laboratory personnel. One plot that may be relatively overlooked is the normal probability plot, which gives a visual snapshot of the distribution of data. It might be a simple way to non-statistically determine whether or not data are normally or non-normally distributed, or if they are bi- or tri-modal, or log-distributed.