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ESD.02 Essentials of Engineering Lecture Notes

Communication: Presentations

Preparation:
Read: Edward R. Tufte, Visual and Statistical Thinking: Displays of Evidence for Making Decisions, Graphics Press, Cheshire, Connecticut, 1997.
Read the case studies of:
Cholera Epidemic Analysis by Snow: good hypothesis and data displayed well in graphic
Challenger Disaster: information was hid in presentation (they were concerned about temperature, but present data chronologically)


As an engineer's career evolves, they will typically find that they will make more and more presentations; for example, CEO's make 2-3 speeches a day.

Technical meetings have gotten to the point where it is expected that all information should be outlined visually (so that people don't have to listen).

However, one should be aware of the limitations of the "PowerPoint Presentation." For a bad example, look here. Graphics should display data, not emotion.

Be concise with your information, but do not try to overload your message. A 20 minute presentation should make one point. An hour long presentation should make two or three.

Two Major Concerns with Displaying Visual Comparisons

  • Multivariate information must be presented on a 2-D plane (flatland)
    Here is a good example of how to do this.
  • Data density must be maximized

    General Principles

  • Enforce visual comparisons
  • Show causality
  • Show multivariates
  • Complete and integrate words, pictures/images and data/numbers
  • Presentations rise and fall on quality, integretity and relevance of the CONTENT
    Metaprinciple:
    Visual information design is controlled by your thinking.
    Ask yourself - what is the intellectual task that this display will help with?
    Bad design is oftenc aused by bad thinking.
  • Better to see info adjacent in space than stacked in time
  • Use small multiples - repeated design is efficient for the viewer

    When Making Decisions:

  • Show the causality!
  • Show all of the data!

    Be Honest in the Presentation of Your Data.
    Do not manipulate your data to adjust reality (see The Log Pig)
    The Conclusions should be Obvious.