This document provides instruction on presenting data in charts, graphs and tables. It discusses the purpose of data visualization and different types of visualizations including line graphs, bar charts, histograms, pie charts, area maps and tables. Examples of each type are provided along with specific rules for constructing them. The document also includes warm up questions to test understanding and instructions for group discussion.

1. Unit 8: Presenting Data in
Charts, Graphs and Tables
#1-8-1

2. Warm Up Questions: Instructions
 Take five minutes now to try the Unit 8 warm
up questions in your manual.
 Please do not compare answers with other
participants.
 Your answers will not be collected or graded.
 We will review your answers at the end of the
unit.
#1-8-2

3. What You Will Learn
 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
#1-8-3

4.  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?
#1-8-4
Analysing Surveillance Data

5. Purpose of Displaying Data
 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
#1-8-5

6. Types of Variables
 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.
#1-8-6

7.  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
General Rules for Displaying Data

8.  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
#1-8-8
Graphs

9. Scale Line Graph
 Scale line graph: represents frequency
distributions over time
 Y-axis represents frequency.
 X-axis represents time.
#1-8-9

10. Example: Scale Line Graph
Figure 8.1. Trends in HIV prevalence among
pregnant women in Country X, years 1 – 10
40
30
20
10
0
1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
%
Source: STD/AIDS Control Programme, Uganda (2001) HIV/AIDS Surveillance Report
#1-8-10
Year

11. Specific Rules: Scale Line Graphs
 Y-axis should be shorter than X-axis
 Start the Y-axis with zero
 Determine the range of values needed
 Select an interval size
#1-8-11

12. Bar Charts
 Uses differently coloured or patterned bars to
represent different classes
 Y-axis represents frequency
 X-axis may represent time or different classes
#1-8-12

13. Example: Bar Chart
Figure 8.2. Differences in HIV prevalence among
various high-risk groups, Country X, year 1.
30
25
20
15
10
5
0
Female sex
workers
Men who
have sex
with men
Injecting drug
users
Prisoners Refugees
Population
% HIV prevalence
#1-8-13

14. Specific Rules: Bar Charts
 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.
#1-8-14

15. Clustered Bar Charts
 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.
#1-8-15

16. Example: Clustered Bar Chart
Figure 8.3. HIV prevalence rate among
pregnant 15- to 19-year-olds at 4 clinic
sites, City X, Country Y, years 1 – 3
#1-8-16
35
30
25
20
15
10
5
0
Site 1 Site 2 Site 3 Site 4
Clinic
Year 1
Year 2
Year 3
HIV prevalence (%)
Source: Ministry of Health, Count ry Y. Annual AIDS Surveillance Report, year 3.

17. Specific Rules:
Clustered Bar Charts
 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.
#1-8-17

18. Histograms
 A representation of a frequency distribution
by means of rectangles
 Width of bars represents class intervals and
height represents corresponding frequency
#1-8-18

19. Example: Histogram
#1-8-19
Figure 7.3. Children Living with HIV,
Figure 8.4. Children living with HIV,
District X, 2002
District X, 2002
160
140
120
100
80
60
40
20
0
<1 1 2 3 4 5 - 9 10 - 13

20. Pie Charts
 A circular (360 degree) graphic
representation
 Compares subclasses or categories to the
whole class or category using differently
coloured or patterned segments
#1-8-20

21. #1-8-21
Example: Pie Chart
Figure 8.5. Projected annual expenditure
requirements for HIV/AIDS care and support
by 2005, by region

22. Area Maps
 A graph used to plot variables by geographic
locations
#1-8-22

23. Example: Area Map
Figure 8.6. HIV Prevalence in Adults
in Africa, end 2003
#1-8-23
Source: UNAIDS, 2003

24. Tables
#1-8-24
 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.

25. #1-8-25
Example: Table
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

26. In Summary
 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.
#1-8-26

27. Warm Up Review
 Take a few minutes now to look back at your
answers to the warm up questions at the
beginning of the unit.
 Make any changes you want to.
 We will discuss the questions and answers in
a few minutes.
#1-8-27

28. Answers to Warm Up Questions
1. List two demographic variables by which
surveillance data can be analysed.
#1-8-28

29. Answers to Warm Up Questions,
Cont.
1. List two demographic variables by which
surveillance data can be analysed. Age, sex,
marital status, etc.
#1-8-29

30. Answers to Warm Up Questions,
Cont.
2. True or false? Compiling all the data into one
comprehensive chart or graph is more
effective than including many simpler
diagrams.
#1-8-30

31. Answers to Warm Up Questions,
Cont.
2. True or false? Compiling all the data into one
comprehensive chart or graph is more
effective than including many simpler
diagrams. False
#1-8-31

32. Answers to Warm Up Questions,
Cont.
3. Which of the following cannot be extracted
from public health surveillance data:
a. changes over time
b. changes by geographic distribution
c. differences according to subject’s sex
d. none of the above
#1-8-32

33. Answers to Warm Up Questions,
Cont.
3. Which of the following can not be extracted
from public health surveillance data:
a. changes over time
b. changes by geographic distribution
c. differences according to subject’s sex
d. none of the above
#1-8-33

34. Answers to Warm Up Questions,
Cont.
4. Match the type of chart/graph with its
example.
#1-8-34

35. Answers to Warm Up Questions,
Cont.
4. Match the type of chart/graph with its
example:
scale line graph: d
area map: c
pie chart: a
histogram: b
#1-8-35

36. Small Group Discussion:
Instructions
 Get into small groups to discuss these
questions.
 Choose a speaker for your group who will
report back to the class.
#1-8-36

37. Small Group Reports
 Select one member from your group to
present your answers.
 Discuss with the rest of the class.
#1-8-37

38. Case Study: Instructions
 Try this case study individually.
 We’ll discuss the answers in class.
#1-8-38

39. Case Study Review
 Follow along as we go over the case study in
class.
 Discuss your answers with the rest of the
class.
#1-8-39

40. Questions, Process Check
 Do you have any questions on the information
we just covered?
 Are you happy with how we worked on Unit 8?
 Do you want to try something different that will
help the group?
#1-8-40