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Arguing with Data: Introduction to Descriptive Data Analysis

Arguing with Data: Introduction to Descriptive Data Analysis. Professor Sarah Reber Lecture 2. Goals of Visualization. Help identify and understand patterns in the data Identify data problems Identify problems with other types of analysis Figure out what the story is

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Arguing with Data: Introduction to Descriptive Data Analysis

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  1. Arguing with Data: Introduction to Descriptive Data Analysis Professor Sarah Reber Lecture 2

  2. Goals of Visualization • Help identify and understand patterns in the data • Identify data problems • Identify problems with other types of analysis • Figure out what the story is • Help others see what you see • Illustrate your story • Highlight important patterns in the data • Make information accessible

  3. Visual Perception • Length and position most precise • Color (if you have it) better than shape • 2 dimensions usually best • We perceive differences at ratios (proportionally) • Shade • Length • Visual complexity is distracting • We can perceive what we are used to more quickly

  4. How to proceed • What is the question? • What do the data say? • What is the answer? • What is my story? • How can I effectively communicate the story/answer? • What aspects of the data do I want to highlight? • What is the best way to do that • Iterate! • Keep coming back to the question

  5. General Principles • Show as much as you need to make the point, no more • Keep your audience in mind • What types of visualizations are they used to • Keep your format in mind • Color or black and white? • Animation? • Multiple formats? • Prioritize function over form • Try, try again

  6. Dos and Don’ts • Label your axes • Limited exceptions: time, other “obvious” scales • Don’t ever use 3D for 2D data • Almost never use 3D at all • Bar chart (or other area graph) axes should always go to 0 • Avoid pie charts • Sort categorical data in some meaningful way • Usually not alpha • Often rank order

  7. Dos and Don’ts • Do not have years (or other numbers) equally spaced on the x axis if the data are not reported at equal intervals • Be careful using “line” charts in Excel • Use scatter instead • Adjust for inflation if you have money over time • Unless your point is about inflation • (come back to this)

  8. X-axis Scaling Data over time

  9. Scales and Transformations Yahoo! finance

  10. http://finance.yahoo.com/echarts?s=msft#symbol=msft;range=1d;compare=;indicator=volume;charttype=area;crosshair=on;ohlcvalues=0;logscale=off;source=undefined;http://finance.yahoo.com/echarts?s=msft#symbol=msft;range=1d;compare=;indicator=volume;charttype=area;crosshair=on;ohlcvalues=0;logscale=off;source=undefined; http://finance.yahoo.com/echarts?s=%5EGSPC#symbol=%5Egspc;range=my;compare=;indicator=volume;charttype=line;crosshair=on;ohlcvalues=0;logscale=on;source=undefined;

  11. Scaling and Transformations Health insurance premiums

  12. Scaling Female shares in the census

  13. Smoothing Quit Rates

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