 |
 |
 |
Unit 7 - Quantitative Data
[ Attention | Objectives | Readings | Assignments | Assessment | Webliography ]
Attention
Visual skills are particularly important in many problem-solving
situations. Once such skill is the ability to quickly see patterns in
information represented visually. See the graphic below:
Derived from Rieber, L. P.(1994). Computers, Graphics, & Learning, p.5.
During this unit, refer to these
often. Be sure that by the end of the unit you have achieved these objectives.
1. Use spreadsheet and graphic software to create visual representation of quantitative data.
2. Describe graphical excellence (Tufte, 1983).
3. Create different types of numerical displays.
4. Determine the integrity of a graphic representation of data (Tufte, 1983).
5.
Represent data graphically to convey a message in different
ways without jeopardizing the integrity of the message.
A checklist of the State Board of Educational Certification Standards addressed in this module is posted at the end of the module. Use this checklist to assess your mastery.
1. Lohr: Chapter 5.
2. Photoshop 15 & 16
Paper:
Selective
Data Analysis, Photo Manipulation, and Stylistic Embellishment for Honest Message
Design
Instructional Content: Envisioning Quantitative Data
Exercise 1
Envisioning Quantitative Data- the information below describes a quantity, labels, and functions. On the piece of scratch paper, thumbnail sketch (create a draft drawing) a visual that conveys all of the information below.
A minimum of 5 officials is needed to officiate the action of 22 football players. The referee, backjudge, linesman, line judge, and umpire are in position to observe formations and play before and after the ball is kicked. In addition, the officials will rule on infractions and will administer the appropriate consequence without preferential treatment.
Most of the information in this unit, the
Graphical Display of Numerical Data, is derived from:
E. R. Tufte. (1983). The Graphical Display of Quantitative Information. Graphics Press.
Graphical Excellence
§ provides efficient communication of complex quantitative ideas
§ provides instruments for reasoning about quantitative information
§ is nearly always multivariate
§ tells the truth
Types
§ data maps
§ time series
§ space-time narratives
§ relational graphics
This is an effective device for enhancing explanatory power. The graphic to the left designed by Minard in 1869 to describe Napolean’s Russian Campaign of 1812 across six variables that are shown graphically. They are army size, location, army’s movement, temperature, dates, advances, and retreat. The multivariate data tells a story.
The above graphic lacks integrity.
Principles for Integrity
§ representation of numbers should be directly proportional to quantities represented,
§ clear labeling and thorough explanations prevent distortion and ambiguity,
§ show data variation, not design variation,
§ do not quote data out of context
Why Do Graphic Designers Lie?
§ Lack of quantitative skills
§ Desire to jazz up the data
§ Desire to simplify the data
Graphical Competence
§ substantive
§ statistical
§ artistic
Design Steps
§ Above all else, show the data
§ Maximize the data-ink ratio
§ Erase non-data-ink
§ Erase redundant data-ink
§ Revise and edit
This graphic presents only three data points, creating a very low density graphic.
In this graphic, all ink represents data, creating a high density graphic.
The following three graphics are described in
the paper, Selective Data Analysis, Photo Manipulation,
and Stylistic Embellishment for Honest Message Design.
Summary
§ Graphical Excellence
§ Graphical Integrity
§ Data-Ink Maximization
§ Selective Data Analysis
Exercise 2
Children’s (1-17) injuries resulting from accidents-USA 1998:
Home injuries 10,000,000
School injuries 3,000,000
Street/highway injuries 2,000,000
Generate 3 different roughs to present the above relational data.
Exercise 3
Comparative Bits of Data
A & M is 4 and 1 so far in the ‘99 season
Generate a rough to present the above bit of data.
Exercise 4
Urban vs. Rural Percentage of the USA Population 1790-1900
|
|
1790 |
1830 |
1870 |
1910 |
1950 |
1990 |
|
Urban (%) |
5.1 |
8.8 |
25.7 |
45.7 |
58.8 |
73.7 |
|
Rural (%) |
94.9 |
91.2 |
74.3 |
54.3 |
41.2 |
26.3 |
Generate 3 different roughs to present the progression of relational data in an artful way.
Assignments (Turn
this in):
Quantitative Data
Obtain a data set relating to educational
research. Print out the data in table form. Produce 2 graphs of the data, which
result in differing interpretations or emotional impact due to varied
dimensions, format, or visual references. The graphs must have
integrity. Move the graphs into a paint and/or draw software to make them
pictographs, manipulate them, and embellish them while maintaining integrity.
Use a graphing utility like Excel to make graphs of publishable quality. Turn in the related data set and
the completed graphs.
Assessment
Quantitative Data Rubric
§ (1 point) Use educational research data.
§ (1 point) Produce two graphs of the data
§ (2 points) Interpret the data from different perspectives or formats .
§ (3 points) Maintain integrity of graphs.
§ (3 points) Create communicative, balanced, unified, and simple graphic screens. Appropriately apply typography and shapes.
View the Instructor-Supplied web site resources and share links to interesting and relevant web sites that you reviewed and found useful for the design and development of computer graphics.