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

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

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What You Will Learn v 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

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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? #1-8-4 Analysing Surveillance Data

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Purpose of Displaying Data v 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

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Types of Variables v 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 v Continuous variables are items that occur in numerical order. #1-8-6

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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. Dont compare variables with different scales of magnitude. #1-8-7 General Rules for Displaying Data

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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

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

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# Year Figure 8.1. Trends in HIV prevalence among pregnant women in Country X, years 1 – 10 Example: Scale Line Graph

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

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

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Example: Bar Chart Figure 8.2. Differences in HIV prevalence among various high-risk groups, Country X, year 1. #1-8-13

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Specific Rules: Bar Charts v Arrange categories that define bars in a natural order (for example, age). v If natural order does not exist, define categories by name, such as country, sex or marital status. v Position the bars either vertically or horizontally. v Make bars the same width. v Length of bars should be proportional to the frequency of event. #1-8-14

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Clustered Bar Charts v Bars can be presented as clusters of sub-groups in clustered bar charts. v These are useful to compare values across categories. v They are sometimes called stacked bar charts. #1-8-15

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

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Specific Rules: Clustered Bar Charts v Show no more than three sub-bars within a group of bars. v Leave a space between adjacent groups of bars. v Use different colours or patterns to show different sub-groups for the variables being shown. v Include a legend that interprets the different colours and patterns. #1-8-17

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

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Example: Histogram # Figure 8.4. Children living with HIV, District X, 2002

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

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

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

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

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Tables # v A rectangular arrangement of data in which the data are positioned in rows and columns. v Each row and column should be labelled. v Rows and columns with totals should be shown in the last row or in the right-hand column.

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# Table 8.1. Adults and children with HIV/AIDS by region in Country Y, end year X Example: Table RegionAdults and adolescents 15 years Children <15 yearsTotal Total

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In Summary v Surveillance data can be analysed by person, place or time. v Depending on your data, you can choose from a variety of chart and graph formats, including pie charts, histograms, tables, etc. v Using several simpler graphics is more effective than attempting to combine all of the information into one figure. #1-8-26

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

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

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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. #1-8-29

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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

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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

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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 subjects sex d. none of the above #1-8-32

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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 subjects sex d. none of the above #1-8-33

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

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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

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

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

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Case Study: Instructions v Try this case study individually. v Well discuss the answers in class. #1-8-38

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

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

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