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

Warm Up Questions: InstructionsTake 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

What You Will LearnBy 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

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?#1-8-4Analysing Surveillance Data

Purpose of Displaying DataThe 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 VariablesCategorical 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

Simpler is better.

Graphs, tables and charts can be used together.

Use clear descriptive titles and labels.

Provide a narrative description of the highlights.

Dont compare variables with different scales of magnitude.

#1-8-7General 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#1-8-8Graphs

Scale Line GraphScale line graph: represents frequency distributions over time

Y-axis represents frequency.

X-axis represents time.#1-8-9

#1-8-10YearFigure 8.1. Trends in HIV prevalence amongpregnant women in Country X, years 1 10 Example: Scale Line Graph

0

10

20

30

40

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

%

Source: STD/AIDS Control Programme, Uganda (2001) HIV/AIDS Surveillance Report

Specific Rules: Scale Line GraphsY-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 ChartsUses 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 ChartFigure 8.2. Differences in HIV prevalence among various high-risk groups, Country X, year 1. #1-8-13

Chart2

24

20

17

28

12

Female sex workers Men who have sex with men Injecting drug users Prisoners Refugees

Population

% HIV prevalence

Sheet1

% HIV prevalencePopulation

24Female sex workers

20Men who have sex with men

17Injecting drug users

28Prisoners

12Refugees

Sheet1

Female sex workers Men who have sex with men Injecting drug users Prisoners Refugees

Population

% HIV prevalence

Sheet2

Sheet3

Specific Rules: Bar ChartsArrange 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 ChartsBars 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

Figure 8.3. HIV prevalence rate among pregnant 15- to 19-year-olds at 4 clinic sites, City X, Country Y, years 1 3#1-8-16Example: Clustered Bar Chart

0

5

10

15

20

25

30

35

Site 1

Site 2

Site 3

Site 4

Clinic

Year 1

Year 2

Year 3

HIV prevalence (%)

Source: Ministry of Health, Country Y. Annual AIDS Surveillance Report, year 3.

Specific Rules: Clustered Bar ChartsShow 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

HistogramsA 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#1-8-19Figure 8.4. Children living with HIV, District X, 2002

Figure 7.3. Children Living with HIV, District X, 2002

5 - 9

10 - 13

Pie ChartsA circular (360 degree) graphic representation

Compares subclasses or categories to the whole class or category using differently coloured or patterned segments#1-8-20

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

Area MapsA graph used to plot variables by geographic locations#1-8-22

Example: Area MapFigure 8.6. HIV Prevalence in Adults in Africa, end 2005#1-8-23Source: UNAIDS, 2006

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

#1-8-25Table 8.1. Adults and children with HIV/AIDS by region in Country Y, end year XExample: Table

In SummarySurveillance 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 ReviewTake 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

Answers to Warm Up Questions1. List two demographic variables by which surveillance data can be analysed. #1-8-28

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

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

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

Answers to Warm Up Questions, Cont.3. Which of the following cannot be extracted from public health surveillance data:a.changes over timeb.changes by geographic distributionc.differences according to subjects sexd. none of the above #1-8-32

Answers to Warm Up Questions, Cont.3. Which of the following can not be extracted from public health surveillance data:a.changes over timeb.changes by geographic distributionc.differences according to subjects sexd. none of the above #1-8-33

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

Answers to Warm Up Questions, Cont.4. Match the type of chart/graph with its example: scale line graph: darea map: cpie chart: ahistogram: b#1-8-35

Small Group Discussion: InstructionsGet 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 ReportsSelect one member from your group to present your answers.

Discuss with the rest of the class. #1-8-37

Case Study: InstructionsTry this case study individually.

Well discuss the answers in class. #1-8-38

Case Study ReviewFollow along as we go over the case study in class.

Discuss your answers with the rest of the class. #1-8-39

Questions, Process CheckDo 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