BASICS OF DATA REPRESENTATION The Search For Well- Designed, Useful, and Ethical Graphs.
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Transcript of BASICS OF DATA REPRESENTATION The Search For Well- Designed, Useful, and Ethical Graphs.
![Page 1: BASICS OF DATA REPRESENTATION The Search For Well- Designed, Useful, and Ethical Graphs.](https://reader036.fdocuments.in/reader036/viewer/2022062421/56649dd05503460f94ac4a89/html5/thumbnails/1.jpg)
BASICS OF DATAREPRESENTATION
The Search For Well-Designed, Useful, and Ethical Graphs
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DIFFERENT TYPES OF GRAPHS• Useful to know the kinds out there to see if the best type of graph has been
chosen to represent the kind of data being presented.
• Comparison Graphs
• Bar
• Line
• Composition Graphs
• Stacked Area
• Pie Charts
• Distribution Graphs
• Line Histographs
• Relationship Graphs
• Scatter Plots
• Bubble Charts
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#1: COMPARISON GRAPHS Show How Variables in a Study Interact
• Useful to show how one or more metrics change over time
• Useful to show correlations and comparisons (such as the rise or Twitter follows after Oscar nominations were announced)
• Useful to compare changes over the same period of time within multiple groups
• Bars are good to show larger changes; Lines are better for shorter changes
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COMPARISON GRAPHS (BAR GRAPHS)
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COMPARISON GRAPHS (BAR GRAPHS)
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COMPARISON GRAPHS (LINE CHARTS)
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#2: COMPOSITION GRAPHSShow How Different
Variables Inform a Whole
• Pie Charts excel at showing how percentages of a whole are allocated (multiples can be used for comparison)
• Stacked Area charts excel at showing compositional changes over time along with the Pie Chart’s allocation metric
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COMPOSITION GRAPHS (STACKED AREA)
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COMPOSITION GRAPHS (PIE)
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COMPOSITION GRAPHS (PIE)
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COMPOSITION GRAPHS (PIE)
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COMPOSITION GRAPHS (PIE)
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#3: DISTRIBUTION GRAPHS
Show How and If Correlations Occur
• Best for showing a single variable with A LOT of data points
• One dimension will always be frequency
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DISTRIBUTION GRAPHS
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DISTRIBUTION GRAPHS
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#4: RELATIONSHIP GRAPHS
Show How Two or More Variable Relate to Each
Other
• Scatter Plots show the correlation of two variables with multiple data points
• Bubble Graphs are like scatter plots for three variables but also quickly show amount through the size of the bubble
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RELATIONSHIP GRAPHS (SCATTER PLOT)
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RELATIONSHIP GRAPHS (BUBBLE GRAPH)
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What are Graphs and Infographics Good At?
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MAKE SOMETHING MORE ABUNDANTLY CLEAR THAN ONLY WORDS COULD EVER DO
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REWORK DATA TO CLEAR UP COMMON CONFUSIONS
Romney/Obama Electoral Map that Could Lead Some to Believe the Country is More Conservative Than Liberal, or Even That Romney Should Have Won.
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REWORK DATA TO CLEAR UP COMMON CONFUSIONS
Electoral Map Redrawn to Reflect Population Sizes of Areas.
Now Map More Clearly Shows Obama’s edge (slight as it was).
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USING VISUAL RHETORIC TO SHOW BIAS (GOOD OR BAD DEPENDING ON CONTEXT)
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Things to Look For, or, Where Graphs Go Wrong.
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#1: COULDA BEEN BETTER
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#2: ???
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#2: LEAVING OUT VALID INFO THAT WOULD HURT YOUR ARGUMENT
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#3: STRAIGHT UP LYING
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#3: STRAIGHT UP LYING
FBI Supplementary Homicide Reports: 1980-2010 (Known Offenders)
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#4: BEING AN IDIOT
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#5: ???
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#5: NOT SHOWING WHOLE GRAPH (UNLIKE THIS ONE)
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#5: NOT SHOWING WHOLE GRAPH
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#5: NOT SHOWING WHOLE GRAPH
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#5: NOT SHOWING WHOLE GRAPH
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#6: FAILING TO PROVIDE A LEGEND (OR A CLEAR ONE)
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#6: FAILING TO PROVIDE A LEGEND (OR A CLEAR ONE)
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#7: ???
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#7: NOT HAVING AXIS GOING IN EXPECTED ORDER AND/ORBEING UNABASHEDLY MANIPULATIVE
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#8:NOT PROVIDING REALLY IMPORTANT CONTEXT
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#9: ???
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#9: UNEQUAL INTERVALS
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#10: DESIGN EFFECTS THAT ONLY CONFUSE
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#10: DESIGN EFFECTS THAT ONLY CONFUSE
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#10: DESIGN EFFECTS THAT ONLY CONFUSE
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#10: DESIGN EFFECTS THAT ONLY CONFUSE
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OVERVIEW QUESTIONS TO ASK• Has the right type of graph been chosen to represent the point the graph is
trying to make? Or could the graph be re-designed to show the point more clearly?
• Is everything labeled clearly? (x/y axes, colors (if they have meaning), title, source of data included with graph, etc.)
• Is the graph showing enough data points and/or range to mean anything useful?
• Is the graph using equal intervals and thusly not skewing the results?
• If 3D or some other effect has been applied, is it helping or hurting?
• Is the graph leaving out information that could hurt its argument?
• Is the graph using any design/images that show inappropriate bias (this depends on the source)?