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QMCS 200

QMCS 200. Types of Charts Graphical Integrity. Today’s Class. Review last TIA homework Review Exam Finish up the first exercise Talk about Network Lab Talk about multi-series charts Talk about graphical integrity Chapter 2, HOE #2. Using Charts: What are we doing?. One series or many?

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QMCS 200

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  1. QMCS 200 Types of Charts Graphical Integrity R. Smith - qmcs 200

  2. Today’s Class • Review last TIA homework • Review Exam • Finish up the first exercise • Talk about Network Lab • Talk about multi-series charts • Talk about graphical integrity • Chapter 2, HOE #2 R. Smith - qmcs 200

  3. Using Charts: What are we doing? • One series or many? • 1 series: it’s easy – stacked and clustered are identical! • Multiple: decide between cluster, stacked, 100% stacked • Looking at absolute or relative values? • Relative numbers: Pie or 100% Stacked Chart • Absolute numbers: Column, Area, Bar, Line, etc. • Categories, or some sort of sequence? • Categories = Column or Bar Chart • Sequence = Line or Area Chart • Comparing category totals or subtotals? • Totals = Stacked Chart • Subtotals = Cluster Chart R. Smith - qmcs 200

  4. Handling multiple series • Graph the dataonly, not the totals! • This throws off the whole appearance of your graph • In a stacked chart, it makes the chart unreadable • Pick the right axis for the chart • What clusters or stacked totals do you want to compare? R. Smith - qmcs 200

  5. Building Good Graphics Some ideas regarding quality graphics • Graphical Integrity • A graphic’s most obvious interpretations must be consistent with the underlying data • Avoid accidental or intentional misrepresentation • Forgo “chartjunk” that draws attention away from the data • Examples: moiré vibration, grids, graphical “ducks” • Maximize the Data-to-Ink ratio • Data-to-Ink Ratio = ink used to print the actual data all ink used to print the graphic R. Smith - qmcs 200

  6. The “Lie Factor” – an example • New York Times, August 9, 1978 R. Smith - qmcs 200

  7. The Lie Factor • Computes the effect of distortion in a quantitative graphic like a chart • Lie Factor = size effect shown in graphic size effect in the data • More than 5% (.95 to 1.05) is substantial • Not caused by errors in drafting • Lie Factors of 2 to 5 are common R. Smith - qmcs 200

  8. Calculating the Lie Factor • Change in fuel economy from 1978-1985 = 53% (0.53) • Change in graphic = change from 0.6” to 5.3” • (5.3 - 0.6)/0.6 = 7.83 = 783% • Lie Factor = 7.83/0.53 = 14.8 -- almost 15 times reality R. Smith - qmcs 200

  9. An Accurate View • Accurate in 2 dimensions • Puts numbers in context by including current and expected average MPG of cars on the road R. Smith - qmcs 200

  10. Good Graphics and Excel • It’s hard to build an inaccurate graph, unless you make a mistake • Including totals, swapping the axes by mistake, etc. • It’s easy to build a “visually busy” graph • Excel “guesses” about colors • You have to adjust things to work with your printing environment • It’s easy to crank up the data-to-ink ratio • 3D graphs are mostly wasted ink • 3D graphs can be misleading, too R. Smith - qmcs 200

  11. Possible Distortions in Excel • Data Problems (GIGO) • Ignoring monetary inflation • Comparing time periods of different durations • Omitting data that provides context • Ignoring other factors that differ in the categories • Visual Problems • Data-to-Ink Ratio – Excel uses lots of ink and color even when not needed • 3D graphics – can visually misrepresent relative values R. Smith - qmcs 200

  12. Examples • The mis-scaled gas mileage • Oil Prices and Inflation • Nobel Prizes and time periods • Context and traffic enforcement • Influences on state budgets • 2D and 3D ambiguities R. Smith - qmcs 200

  13. Oil Prices and Inflation R. Smith - qmcs 200

  14. Inconsistent Time Periods • National Science Foundation, 1974 R. Smith - qmcs 200

  15. Inconsistent Time Periods • National Science Foundation, 1974 R. Smith - qmcs 200

  16. Context is Essential • Two data points can’t possibly tell the story alone R. Smith - qmcs 200

  17. So, what’s the real story? • Different contexts yield different interpretations • Is this a blip, or a real change, or part of a cycle? R. Smith - qmcs 200

  18. Connecticut Statistics • Actually, drop was a return to previous levels • “Why did deaths go up 1954-56?” R. Smith - qmcs 200

  19. Regional Statistics • Compare per capita deaths in region over nearby years • All states enjoyed a reduction, not just the state that cracked down R. Smith - qmcs 200

  20. Budget Inflation Revisited • New York State budgets and aid to municipalities • Dramatic growth, right? R. Smith - qmcs 200

  21. Visual Trickery • Material on left, and perspective on early years make them appear small • Horizontal arrows emphasize small size • Perspective makes the rightmost cluster stand forward, looking extra large • Vertical arrows emphasize height R. Smith - qmcs 200

  22. Reducing Data-to-Ink Ratio • If we take out the extra graphics and perspective (left) we yield a simple story (right) • But the story is still misleading R. Smith - qmcs 200

  23. Adjusting for Change • Take into account both inflation and population change • This story shows no significant changes in 7 years R. Smith - qmcs 200

  24. A 2-D Graphics Problem • Washington Post, October 25, 1978 • Inflation is one-dimensional • Shrinking money in 2 dimensions is misleading • Dollar’s area should reflect its purchasing power • The 1978 dollar should be about twice as large as shown R. Smith - qmcs 200

  25. A 3-D Graphics Problem • Problem with 3D image • Prices increased 454% • Graphic size: 4,280% • Lie Factor = 9.4 • If we take the “barrel metaphor” seriously, the barrel volume increases 27,000% • Lie Factor = 59.4 R. Smith - qmcs 200

  26. Excel 3D Pie Chart • Gives Denver (19%) more ink than Miami (21%) • Makes Boston look overwhelming • Makes New York look much less pitiful R. Smith - qmcs 200

  27. Minimizing Data to Ink Ratio • How much ink do you really need to display the data you have? • Extra ink is chartjunk • Makes the chart feel like it says more that it really does • A checklist • Extra “dimensions” like 3D blocks in a 2D bar chart • Shaded backgrounds – do they make the data easier to see, or do they waste ink? • Grid lines – do they really help people compare the data? R. Smith - qmcs 200

  28. For More Information • Edward Tufte’s The Visual Display of Quantitative Information • Chapter 2: “Graphical Integrity” • Also, notes from other chapters • www.edwardtufte.com R. Smith - qmcs 200

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