Graphing Appendix 469
Some bar graphs are constructed so that their bars
run horizontally instead of vertically (Figure A.7). Note
that in contrast to Figure A.6, in this case the x-axis por-
trays the numeric variable (population percentage) and
the y-axis portrays the categorical variable (discrete age
ranges). Also note that bars extend from their central
value of zero on the x-axis to the right to display the nu-
meric values for females, and to the left to display the
numeric values for males. In this horizontal orientation,
the numeric value of each bar is determined by its length
rather than its height. By ex-
amining this graph we can in-
fer that Ethiopia’s population
is likely to keep growing rap-
idly because the majority of its
males and females are in the
younger, pre-reproductive age
categories.
A pie chart shows the pro-
portion of some total value
taken up by two or more differ-
ent categories. Each category is
graphically portrayed as a “slice”
of the total (the entire “pie”),
and the size of each of these slic-
es corresponds to its proportion
0
2
4
6
8
Per capita ecological
footprint (hectares/person)
India France United
States
10
Based on data from World Wildlife Fund,
Living Planet
Report, 2008.
Male Female
Bars run
horizontally
Rapid growth:
Ethiopia
Age
100+
75–79
80–84
85–89
90–94
95–99
70–74
65–69
60–64
55–59
50–54
45–49
40–44
35–39
30–34
25–29
20–24
15–19
10–14
5–9
0–4
Central value
10
Percentage of population
8 6 4 2 0 2 4 6 8 10
Based on data from Population Reference Bureau.
A bar graph is often used when one variable is a num-
ber and the other variable is a category. For example,
the bar graph below shows how a numeric variable (per
capita ecological footprint) varies across a categorical vari-
able (country). In such cases the height of each bar rep-
resents the numeric value for each category. Thus in this
case (Figure A.6) we can see that the per capita ecological
footprint in the United States is more than twice as great
as France’s and more than five times greater than India’s.
of the whole. In the pie chart below (Figure A.8), we can
readily see from the size of the different slices that the
mining industry generates over three-quarters of the to-
tal amount of solid waste we produce, and that less than
2 percent of this waste comes from municipal sources. By
examining the second pie chart that illustrates the pro-
portional contribution of the different materials within
the municipal solid waste slice, we can also see that pa-
per and paperboard make up almost a third of the entire
municipal waste category.
}ÕÀiÊ°ÈÊUÊ >ÀÊÀ>«
Figure A.7
Mining
76%
Agriculture
13%
Municipal
solid waste
1.5%
a. Composition of Total Solid Waste, 2010
Industry
9.5%
b. Composition of Municipal Solid Waste, 2010
Food
waste
13.9%
Plastics
12.4%
Metals
9.0%
Glass
Wood 4.6%
6.4%
Rubber,
leather and
textiles
8.4%
Other
3.4%
Paper and
paperboard
28.5%
Yard
waste
13.4%
Based on data from United States Environmental Protection Agency (EPA), 2010. Based on data from United States Environmental Protection Agency (EPA), 2010.
}ÕÀiÊ°nÊUÊ*iÊ
>ÀÌ