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

```Unit 8: Presenting Data in
Charts, Graphs and Tables
#1-8-1
Warm Up Questions: Instructions

Take five minutes now to try the Unit 8 warm

participants.


unit.
#1-8-2
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
Analysing Surveillance Data
 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
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
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
General Rules for Displaying Data

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
Graphs

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
Scale Line Graph

Scale line graph: represents frequency
distributions over time

Y-axis represents frequency.

X-axis represents time.
#1-8-9
Example: Scale Line Graph
Figure 8.1. Trends in HIV prevalence among
pregnant women in Country X, years 1 – 10
40
30
% 20
10
Year
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
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
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
Example: Bar Chart
Figure 8.2. Differences in HIV prevalence among
various high-risk groups, Country X, year 1.
% H IV p rev alen ce
30
25
20
15
10
5
0
F em ale s ex
M en w ho
Injec ting drug
w ork ers
have s ex
us ers
P ris oners
R efugees
w ith m en
P o p u la tio n
#1-8-13
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
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
Example: Clustered Bar Chart
HIV prevalence (%)
Figure 8.3. HIV prevalence rate among
pregnant 15- to 19-year-olds at 4 clinic
sites, City X, Country Y, years 1 – 3
Yea r 1
Yea r 2
Yea r 3
35
30
25
20
15
10
5
0
Site 1
Site 2
Site 3
Site 4
Clinic
Source : Ministry of Health, Count ry Y. Annual AIDS Surve illa nce Report, y ear 3.
#1-8-16
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
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
Example: Histogram
Figu8.4.
re 7.3.
Childr en
Living
HIV,
Figure
Children
living
withwith
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
#1-8-19
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
Example: Pie Chart
Figure 8.5. Projected annual expenditure
requirements for HIV/AIDS care and support
by 2005, by region
#1-8-21
Area Maps

A graph used to plot variables by geographic
locations
#1-8-22
Example: Area Map
Figure 8.6. HIV Prevalence in Adults
in Africa, end 2003
Source: UNAIDS, 2003
#1-8-23
Tables

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.
#1-8-24
Example: Table
Table 8.1. Adults and children with HIV/AIDS
by region in Country Y, end year X
Region
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
7 086 800
948 200
8 035 000
Total
#1-8-25
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
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
1. List two demographic variables by which
surveillance data can be analysed.
#1-8-28
Cont.
1. List two demographic variables by which
surveillance data can be analysed. Age, sex,
marital status, etc.
#1-8-29
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
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
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
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
Cont.
4. Match the type of chart/graph with its
example.
#1-8-34
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
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
Small Group Reports

Select one member from your group to

Discuss with the rest of the class.
#1-8-37
Case Study: Instructions

Try this case study individually.

We’ll discuss the answers in class.
#1-8-38
Case Study Review

Follow along as we go over the case study in
class.

class.
#1-8-39
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
```