As discussed
in the section on variables in Chapter 1, quantitative variables
are variables measured on a numeric scale. Height, weight, response
time, subjective rating of pain, temperature, and score on an exam
are all examples of quantitative variables. Quantitative variables
are distinguished from categorical (sometimes called qualitative)
variables such as favorite color, religion, city of birth, and favorite
sport in which there is no ordering or measuring involved.

There are many types of graphs that can be used
to portray distributions of quantitative variables. The upcoming
sections cover the following types of graphs: (1) stem and leaf
displays, (2) histograms, (3) frequency polygons,
(4) box plots, (5) bar charts, (6) line graphs, (7) scatter plots (discussed in a different chapter), and (8) dot plots. Some graph types such as
stem and leaf displays are best-suited for small to moderate
amounts of data, whereas others such as histograms are best-suited
for large amounts of data. Graph types such as box plots are
good at depicting differences between distributions. Scatter plots
are used to show the relationship between two variables.