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220 Part IV: Quality Assurance
Dot Plot
A dot plot is one of the easiest graphs to construct. In a dot plot each observation
is plotted on a real line. For illustration consider Example 18.18.
Dot plots are more useful when the sample size is small. A dot plot gives us,
for example, information about how far the data are scattered and where most
of the observations are concentrated. For instance, in Example 18.17, we see that
the minimum number of defective motors and the maximum number of defective
motors received in any shipment was 5 and 29 respectively. Also, we can see that
75 percent of the time the number of defective motors was between 8 and 21 for
the shipment, and so on.
Pie Chart
Pie charts are commonly used to represent different categories of a population
that are created by a characteristic of interest of that population. For example, allocation
of federal budget by sector, revenues of a large manufacturing company by
region or by plant, technicians in a large corporation who are classified according
to their basic qualification, that is, high school diploma, associate degree, undergraduate
degree, or graduate degree, and so on. The pie chart helps us to better
understand at a glance the composition of the population with respect to the characteristic
of interest.
To construct a pie chart, divide a circle into slices such that each slice represents
a category and is proportional to the size of that category. Remember, the
total angle of the circle is 360 degrees. The angle of a slice corresponding to a given
category is determined as follows:
Part IV.A.4
EXAMPLE 18.18
The following data give the number of defective motors received in 20 different
shipments:
8 12 10 16 6 25 21 15 17 5
26 21 29 8 10 21 10 17 15 13
Construct a dot plot for this data.
Solution:
To construct a dot plot first draw a horizontal line, the scale of which begins at the smallest
observation (5 in this case) or smaller and ends with the largest observation (29 in
this case) or larger (see Figure 18.8).
4 8 12 16 20 24 28 30
Defective motors
Figure 18.8 Dot plot for the data on defective motors received in 20 different shipments.