Visual and Statistical Thinking

Display architecture recapitulates quantitative thinking; design quality grows from intellectual quality.  Such dual principles – both for reasoning about statistical evidence and for the design of statistical graphics – include:

  1. documenting the sources and characteristics of the data
  2. insistently enforcing appropriate comparisons
  3. demonstrating mechanisms of cause and effect
  4. expressing those mechanisms quantitatively
  5. recognizing the inherently multivariate nature of analytic problems
  6. inspecting and evaluating alternative explanations

When consistent with the substance and in harmony with the content, information displays should be documentary, comparative, causal and explanatory, quantified, multivariate, exploratory, skeptical.

   ~ Edward Tufte, Visual and Statistical Thinking


Algorithm Design

Perhaps the most important principle for the good algorithm designer is to refuse to be content.

   ~ Aho, Hopcroft, and Ullman, The Design and Analysis of Computer Algorithms, 1974



The connections between data and decisions are built one good question at a time until understanding bridges the gap between them.