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The Art of Graphical Presentation. Types of Variables Guidelines for Good Graphics Charts Common Mistakes in Graphics Pictorial Games Special-Purpose Charts. Types of Variables. Qualitative Ordered (e.g., modem, Ethernet, satellite) Unordered (e.g., CS, math, literature) Quantitative

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The Art of Graphical Presentation


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    1. The Art of Graphical Presentation • Types of Variables • Guidelines for Good Graphics Charts • Common Mistakes in Graphics • Pictorial Games • Special-Purpose Charts

    2. Types of Variables • Qualitative • Ordered (e.g., modem, Ethernet, satellite) • Unordered (e.g., CS, math, literature) • Quantitative • Discrete (e.g., number of terminals) • Continuous (e.g., time)

    3. Charting Based on Variable Types • Qualitative variables usually work best with bar charts or Kiviat graphs • If ordered, use bar charts to show order • Quantitative variables work well in X-Y graphs • Use points if discrete, lines if continuous • Bar charts sometimes work well for discrete

    4. Guidelines for Good Graphics Charts • Principles of graphical excellence • Principles of good graphics • Specific hints for specific situations • Aesthetics • Friendliness

    5. Principlesof Graphical Excellence • Graphical excellence is the well-designed presentation of interesting data: • Substance • Statistics • Design

    6. Graphical Excellence (2) • Complex ideas get communicated with: • Clarity • Precision • Efficiency

    7. Graphical Excellence (3) • Viewer gets: • Greatest number of ideas • In the shortest time • With the least ink • In the smallest space

    8. Graphical Excellence (4) • Is nearly always multivariate • Requires telling truth about data

    9. Principles of Good Graphics • Above all else show the data • Maximize the data-ink ratio • Erase non-data ink • Erase redundant data ink • Revise and edit

    10. Above All ElseShow the Data

    11. Above All ElseShow the Data

    12. Maximize theData-Ink Ratio

    13. Maximize theData-Ink Ratio

    14. Erase Non-Data Ink

    15. Erase Non-Data Ink North West East

    16. Erase Redundant Data Ink North West East

    17. Erase Redundant Data Ink North West East

    18. Revise and Edit

    19. Revise and Edit

    20. Revise and Edit

    21. Revise and Edit

    22. Revise and Edit

    23. Revise and Edit

    24. Specific Things to Do • Give information the reader needs • Limit complexity and confusion • Have a point • Show statistics graphically • Don’t always use graphics • Discuss it in the text

    25. Give Informationthe Reader Needs • Show informative axes • Use axes to indicate range • Label things fully and intelligently • Highlight important points on the graph

    26. Giving Informationthe Reader Needs

    27. Giving Informationthe Reader Needs

    28. Limit Complexityand Confusion • Not too many curves • Single scale for all curves • No “extra” curves • No pointless decoration (“ducks”)

    29. Limiting Complexityand Confusion

    30. Limiting Complexityand Confusion

    31. Have a Point • Graphs should add information not otherwise available to reader • Don’t plot data just because you collected it • Know what you’re trying to show, and make sure the graph shows it

    32. Having a Point • Sales were up 15% this quarter:

    33. Having a Point

    34. Having a Point

    35. Having a Point

    36. Show Statistics Graphically • Put bars in a reasonable order • Geographical • Best to worst • Even alphabetic • Make bar widths reflect interval widths • Hard to do with most graphing software • Show confidence intervals on the graph • Examples will be shown later

    37. Don’t AlwaysUse Graphics • Tables are best for small sets of numbers • e.g., 20 or fewer • Also best for certain arrangements of data • e.g., 10 graphs of 3 points each • Sometimes a simple sentence will do • Always ask whether the chart is the best way to present the information • And whether it brings out your message

    38. Text Would HaveBeen Better

    39. Discuss It in the Text • Figures should be self-explanatory • Many people scan papers, just look at graphs • Good graphs build interest, “hook” readers • But text should highlight and aid figures • Tell readers when to look at figures • Point out what figure is telling them • Expand on what figure has to say

    40. Aesthetics • Not everyone is an artist • But figures should be visually pleasing • Elegance is found in • Simplicity of design • Complexity of data

    41. Principles of Aesthetics • Use appropriate format and design • Use words, numbers, drawings together • Reflect balance, proportion, relevant scale • Keep detail and complexity accessible • Have a story about the data (narrative quality) • Do a professional job of drawing • Avoid decoration and chartjunk

    42. Use Words, Numbers, Drawings Together • Put graphics near or in text that discusses them • Even if you have to murder your word processor • Integrate text into graphics • Tufte: “Data graphics are paragraphs about data and should be treated as such”

    43. Reflect Balance, Proportion, Relevant Scale • Much of this boils down to “artistic sense” • Make sure things are big enough to read • Tiny type is OK only for young people! • Keep lines thin • But use heavier lines to indicate important information • Keep horizontal larger than vertical • About 50% larger works well

    44. Poor Balanceand Proportion • Sales in the North and West districts were steady through all quarters • East sales varied widely, significantly outperforming the other districts in the third quarter

    45. Better Proportion • Sales in the North and West districts were steady through all quarters • East sales varied widely, significantly outperforming the other districts in the third quarter

    46. Keep Detail and Complexity Accessible Make your graphics friendly: • Avoid abbreviations and encodings • Run words left-to-right • Explain data with little messages • Label graphic, don’t use elaborate shadings and a complex legend • Avoid red/green distinctions • Use clean, serif fonts in mixed case

    47. An Unfriendly Graph

    48. A Friendly Version

    49. Even Friendlier

    50. Have a Story About the Data (Narrative Quality) • May be difficult in technical papers • But think about why you are drawing graph • Example: • Performance is controlled by network speed • But it tops out at the high end • And that’s because we hit a CPU bottleneck