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== 2.2#h(0.6em)Quantitative Variables


    #notebox("Note", rgb("#8a94a6"), rgb("#556666"), rgb("#f7f8fa"))[
#emph[Prerequisites]


      Variables
]


    + Stem and Leaf Displays
+ Histograms
+ Frequency Polygons
+ Box Plots
+ Box Plot Demonstration
+ Bar Charts
+ Line Graphs
+ Dot Plots


    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.