Psych 208A: Proseminar on
Data Analysis & Visualization

Professor Forrest Young

Truth & Consequences

Outline of introductory lecture for Proseminar on Data Analysis and Visualization.


  1. Everything is illusion

  2. The statement "everything is illusion" is itself an illusion. So is this statement ... etc., etc...

  3. Rational-Scientific search for truth is not convergent (over time). Analogy: Hill climbing algorithm trying to find the highest point of the ocean. Even on land, the landscape changes slowly over time.

  4. The scientific method is useful, however. It has provided an understanding of realilty which has been beneficial to mankind for the last 200 years. Will it continue to do so?

  5. The final and most important truth: In their book "Mathematics and the Imagination", Edward Kasner and James Newman call this formula "elegant, concise and full of meaning". They also quote a remark by Benjamin Peirce, the Harvard Mathematician, "Gentleman", he said, after writing this formula on the blackboard, "that is surely true, but is is absolutely paradoxical; we cannot understand it, and we don't know what it means, but we have proved it, and therefore we know it must be the truth."


  1. I play ... I work ...
    I take my work seriously ... but not too ...
    I do what I do because it is fun ... and because its useful.
    (but, it's all an illusion)!
  2. I enjoy mathematics.

    Mathematical systems are internally consistent artificial systems with their own complete reality (though clearly, not real reality).

    But, Godel's proof lets us know that a mathematical system can't be both internally consistent and complete (sigh...)

    Keep in mind, though, that mathematics for its own sake isn't the goal in applied mathematical fields like Statistics and Psychometrics. We must always be able to relate the mathematics to reality (the real reality) so that we can determine its usefulness. And when the further development of a mathematical system isn't useful we should move on to something else. (See my adobe acrobat notes on The Future of Psychometrics).

  3. I particulary enjoy programming.

    With programming, things are clearly right or wrong --- no gray --- all black and white.

    Unfortunately, that's not really true at advanced levels. With complicated programming systems all you know for sure is that the system isn't right! The probability that there are bugs is so close to one that you just know they are lurking around somewhere!

  4. But most of all, I like Data Analysis and Visualization.

    I think the biggest problem in the social sciences is that researchers either study meaningful questions sloppily, or meaningless questions carefully.

    I believe that Data Analysis and Visualization can help researchers in the social sciences optain carefully reasoned answers to their carefully constructed scientific questions: Meaningful answers to meaningful questions.

    I enjoy Data Analysis and Visualization because I enjoy helping others find meaningful answers to meaningful questions.

    What I enjoy most is inventing methods that have the potential to improve and expand the kinds of meaningful answers that people can obtain to their meaningful questions.

The Moral of the Story

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