Courses/Computer Science/CPSC 203/CPSC 203 2007Fall L04/CPSC 203 2007Fall L04 Lectures/Lecture 8

Lecture 8
We expand our "visual review of data analysis", introduce the notion of samples and populations, introduce basic principles for visual display of quantitative information (i.e. charting).

The objectives of today's class are:


 * House Keeping
 * Announce Lab Quiz Reschedule
 * Next Tuesday -- Will briefly Cover Lookup Tables, If ... Then and Pivot Tables as lead in to Databases.
 * Update on Practice Quizzes and Lab IT


 * Topics
 * Continuation of visual introduction to data analysis
 * Principles for Quantitative Display of Visual Information
 * Notion of an "Information Dashboard"
 * Who Are We Survey Exploration

Lecture Glossary

 * Population
 * Sample
 * Random Sample
 * Classification
 * "Curve Fitting" (aka Regression, Ordination ...)
 * Data Ink
 * Chart Junk

Visual Display of Information
Two Critical Principles in the Visual Display of Information are:
 * Statistical Accuracy (the numbers are the "right" numbers, correctly calculated given the data population/sample you are using).
 * Cognitive Effect (the pattern in the data is made clear as possible to the viewer).

Design Issues in the Visual Display of Information (or the World According to Tufte)
 * 1) Maximize Data Ink -- Ink that directly conveys information about data points
 * 2) Minimize Chart Junk -- All additional glyphs, bells, whistles, 3D effects that do not directly convey data information.
 * 3) Use Small Multiples to deal with Complexity -- Create a basis for comparison in large or complex data sets by creating simple diagrams with common aces or common design elements.
 * 4) Data Density -- Very large data sets or very complex data sets require us to find visual techniques that maintain the content of the data, but allow us to get a "gestalt" view that can not be obtained from reading a massive data table.
 * 5) Multiple Use -- If possible put visual elements to multiple uses. Data points, could also be numbers reflecting data values. Data glyphs could reflect relationships between the data attributes in frame, and other data attributes.
 * 6) Aesthetics -- The same principles that make various art constructs effective apply also to visualization of data. Example -- use of the "Golden Rectangle" for 2 D displays. http://en.wikipedia.org/wiki/Golden_rectangle

Bad Chart Examples
http://j-walkblog.com/index.php?/weblog/posts/bad_charts/

http://lilt.ilstu.edu/gmklass/pos138/datadisplay/badchart.htm

Good Chart Examples
http://lilt.ilstu.edu/gmklass/pos138/datadisplay/sections/goodcharts.htm

http://www.compassgr.com/sites/mark/index.htm

Information Dashboard
 "Visual Display

 of the most important information needed to achieve one or more objectives 

 which fits entirely on a single computer screen 

 so it can be monitored at a glance 

.... Stephen Few

Few's 13 Mistakes in Dashboard Design

 * Exceeding the Boundaries of a Single Screen
 * Supplying Inadequate Context for the Data
 * Displaying Excessive Detail or Precision
 * Choosing a Deficient Measure
 * Choosing an Inapropriate Display Media
 * Introducing Meaningless Variety
 * Using Poorly Designed Display Media
 * Encoding Quantitiative Data Innacurately
 * Arranging the Data Poorly
 * Highlighting Important Data Innefectively or Not at All
 * Cluttering the Display with Useless Decoration
 * Misusing or Overusing Color
 * Designing an Unattractive Visual Display

.... If you understand the 6 principles of Visual Display of Information .... you are much less likely to make these 13 mistakes.

Resources
The Visual Display of Quantitiative Information. 1983. By Edward R. Tufte. See also the Tufte Web Site http://www.edwardtufte.com/tufte/

A good article on Tufte appears in the online magazine, Salon, at http://www.salon.com/march97/tufte970310.html

The Elements of Graphing Data. 1985. By William S. Cleveland.

Information Dashboard Design. The Effective Visual Communication of Data. 2006. By Stephen Few.