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# Graphic Presentation Of Data

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• ### Transcript

• 1. Graphic Presentation of Data
• 2. Purpose of a Graph
• A visual presentation of data
• Relationships & comparisons are visual
• Not as daunting as a table of numbers
• Allows some artistry and creativity
• Accuracy is important
• Style of graph must match
• Level of Measurement of the variable(s)
• Nature of this particular data set
• 3. Graphs for Discrete Data
• Data are in categories
• Nominal
• Ordinal if the number of categories is small
• Types of graph:
• Pie Chart
• Bar Chart
• Graph shows the distribution of cases (scores) per category
• Label the categories
• Show the Frequency (count) or Percent
• 4. Pie Chart
• Area of pie = 100%
• Each wedge is in proportion to the percentage for that category
• Labels show count or percent
• Ten slices is about the most to use
• 5. Pie chart methods can also obscure the pattern in the data
• 6. Many problems in this graph!
• 7. Bar Chart
• Area of bars combined is 100%
• Area of each bar is proportional to its percent of total
• Bars do not touch because categories are discrete.
• Many variations; this is the most simple.
• 8. Some graphic methods obscure the trends in the data: BAD IDEA!
• 9. Pictograph: equal size pictures not a problem
• 10. Unequal pictures make for an inaccurate graph
• 11. Which tree does your eye go to first? Which is most prominent? Which has highest count?
• 12. What problems can you identify in this graph?
• 13. Graphs for Continuous Data (Sometimes Ordinal)
• Horizontal axis goes from low to high
• Intervals shown for Interval or Ratio data
• Some ordinal data also graphed this way (e.g., strongly agree, agree, slightly agree, etc)
• Graph shows continuity of the construct
• Histogram: bars that touch at real limits
• Line graph: covers range (a.k.a. Frequency Polygon)
• 14. Histogram
• Ranges of scores grouped together
• Ranges equal width whenever possible
• Labels show mid-point or real limits
• Low scores on left, high scores on right
• 15. What’s wrong with this histogram?
• 16. Check all the details!
• 17. Line Graphs / Frequency Polygon
• Horizontal axis goes from low to high
• Line shows level for each value
• Frequency count
• Percentage
• (Sometimes) average
• Only suitable for Interval or Ratio data
• 18. Editorializing the Data is improper
• 19. Using 3D multiplies the impact and leads to inaccurate interpretation
• 20. Which problem(s) are here?
• 21. Where is the 0% point on this graph? Is work increasing or decreasing? What do the lines represent? What do the people and the bus add to our knowledge?
• 22. Why doesn’t this graph look like GROWTH? (Hint: check out the axes)
• 23. Population Map outside T 3649 Area=population, displayed by location. Great!
• 24. Any questions?
• 25. Keep your eyes open for bad graphs. They’re everywhere!! (You may find some excellent ones too...) For next week: Chapter 3 on Summarizing data Central Tendency (Averages)