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

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Unit 8: Presenting Data in Charts, Graphs and Tables
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Warm Up Questions: Instructions

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 Year #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. #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
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

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 Figure 8.4. Children living with HIV, District X, 2002 #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
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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 Adults and adolescents ≥ 15 years Children <15 years Total 1 14 800 200 15 000 2 20 000 3 3 000 4 5 40 000 6 35 000 7 10 000 8 9 10 5 000 #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

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 time b. changes by geographic distribution c. differences according to subject’s sex d. 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 time b. changes by geographic distribution c. differences according to subject’s sex d. 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: 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 present your answers. 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.