Unit 8 presenting data in charts, graphs and tables

Unit 8: Presenting Data in
Charts, Graphs and Tables
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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.
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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
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 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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Analysing Surveillance Data

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
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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.
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 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.
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General Rules for Displaying Data

 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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Graphs

Scale Line Graph
 Scale line graph: represents frequency
distributions over time
 Y-axis represents frequency.
 X-axis represents time.
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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
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Year

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
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Bar Charts
 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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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
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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.
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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.
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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
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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.

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.
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Histograms
 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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Example: Histogram
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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

Pie Charts
 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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Example: Pie Chart
Figure 8.5. Projected annual expenditure
requirements for HIV/AIDS care and support
by 2005, by region

Area Maps
 A graph used to plot variables by geographic
locations
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Example: Area Map
Figure 8.6. HIV Prevalence in Adults
in Africa, end 2003
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Source: UNAIDS, 2003

Tables
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 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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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

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.
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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.
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Answers to Warm Up Questions
1. List two demographic variables by which
surveillance data can be analysed.
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Answers to Warm Up Questions,
Cont.
1. List two demographic variables by which
surveillance data can be analysed. Age, sex,
marital status, etc.
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Cont.
2. True or false? Compiling all the data into one
comprehensive chart or graph is more
effective than including many simpler
diagrams.
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Cont.
2. True or false? Compiling all the data into one
comprehensive chart or graph is more
effective than including many simpler
diagrams. False
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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
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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
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Cont.
4. Match the type of chart/graph with its
example.
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Cont.
4. Match the type of chart/graph with its
example:
scale line graph: d
area map: c
pie chart: a
histogram: b
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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.
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Small Group Reports
 Select one member from your group to
present your answers.
 Discuss with the rest of the class.
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Case Study: Instructions
 Try this case study individually.
 We’ll discuss the answers in class.
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Case Study Review
 Follow along as we go over the case study in
class.
 Discuss your answers with the rest of the
class.
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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?
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Unit 8 presenting data in charts, graphs and tables

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