LE 4000

1. Presenting and Discussing
Data in Charts, Graphs and
Tables

2.  By the end of this unit you should be able
to:
 list the variables for analysing surveillance data
 identify the types of charts and graphs and when
the use of each is appropriate
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3.  Person: Who develops a disease (for example, by
age group or sex)? Are the distributions changing
over time?
 Place: Where are cases occurring? Is the
geographical distribution changing over time?
 Time: Is the number of reported cases changing
over time?
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4.  The purpose of developing clearly
understandable tables, charts and graphs
is to facilitate:
 analysis of data
 interpretation of data
 effective, rapid communication on complex
issues and situations
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5.  Categorical variables refer to items that
can be grouped into categories.
Ordinal variables are those that have a natural
order.
Nominal variables represent discrete
categories without a natural order.
 Dichotomous variables have only two categories
 Continuous variables are items that occur
in numerical order.
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6.  Simpler is better.
 Graphs, tables and charts can be used together.
 Use clear descriptive titles and labels.
 Provide a narrative description of the highlights.
 Don’t compare variables with different scales of
magnitude. #1-8-7

7.  A diagram shown as a series of one or more
points, lines, line segments, curves or areas
 Represents variation of a variable in comparison
with that of one or more other variables
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8.  Scale line graph: represents frequency
distributions over time
 Y-axis represents frequency.
 X-axis represents time.
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9. #1-8-10
Year
Figure 8.1. Trends in HIV prevalence among
pregnant women in Country X, years 1 – 10

10.  Y-axis should be shorter than X-axis
 Start the Y-axis with zero
 Determine the range of values needed
 Select an interval size
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11.  Uses differently coloured or patterned bars
to represent different classes
 Y-axis represents frequency
 X-axis may represent time or different
classes
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12. 0
5
10
15
20
25
30
Female sex
workers
Men who
have sex
with men
Injecting drug
users
Prisoners Refugees
Population
%HIVprevalence
Figure 8.2. Differences in HIV prevalence among
various high-risk groups, Country X, year 1.
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13.  Arrange categories that define bars in a natural order
(for example, age).
 If natural order does not exist, define categories by
name, such as country, sex or marital status.
 Position the bars either vertically or horizontally.
 Make bars the same width.
 Length of bars should be proportional to the frequency
of event.
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14.  Bars can be presented as clusters of sub-
groups in clustered bar charts.
 These are useful to compare values across
categories.
 They are sometimes called stacked bar
charts.
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15. Figure 8.3. HIV prevalence rate among
pregnant 15- to 19-year-olds at 4 clinic
sites, City X, Country Y, years 1 – 3
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16.  Show no more than three sub-bars within a
group of bars.
 Leave a space between adjacent groups of bars.
 Use different colours or patterns to show
different sub-groups for the variables being
shown.
 Include a legend that interprets the different
colours and patterns.
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17.  A representation of a frequency distribution
by means of rectangles
 Width of bars represents class intervals and
height represents corresponding frequency
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18. Example: Histogram
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Figure 8.4. Children living with HIV,
District X, 2002

19.  A circular (360 degree) graphic
representation
 Compares subclasses or categories to the
whole class or category using differently
coloured or patterned segments
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20. #1-8-21
Figure 8.5. Projected annual expenditure
requirements for HIV/AIDS care and support
by 2005, by region

21.  A graph used to plot variables by
geographic locations
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22. Figure 8.6. HIV Prevalence in Adults
in Africa, end 2003
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Source: UNAIDS, 2003

23.  A rectangular arrangement of data in
which the data are positioned in rows and
columns.
 Each row and column should be labelled.
 Rows and columns with totals should be
shown in the last row or in the right-hand
column.
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24. #1-8-25
Table 8.1. Adults and children with HIV/AIDS
by region in Country Y, end year X
Region Adults and adolescents 15≥
years
Children <15 years Total
1 14 800 200 15 000
2 400 000 20 000 420 000
3 997 000 3 000 1 000 000
4 985 000 15 000 1 000 000
5 1 460 000 40 000 1 500 000
6 465 000 35 000 500 000
7 940 000 10 000 950 000
8 380 000 220 000 600 000
9 900 000 600 000 1 500 000
10 545 000 5 000 550 000
Total 7 086 800 948 200 8 035 000

25.  Surveillance data can be analysed by
person, place or time.
 Depending on your data, you can choose
from a variety of chart and graph formats,
including pie charts, histograms, tables,
etc.
 Using several simpler graphics is more
effective than attempting to combine all
of the information into one figure.
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