Data Simplification Quotes

Simplification seems to be the removal of objects for the goal of making a graphic as clean and uncluttered as possible. Whereas, with optimization, it feels like there's more intelligence in that. It maintains the usability, but tries to distill something down to its essence. But with some data-sets you have to be careful because, as with linear, print journalism, it's easy to shave off facts that don't quite fit the flow.

All knowledge is gained through an orderly loss of information.

Science itself, therefore, may be regarded as a minimal problem, consisting of the completest possible presentment of facts with the least possible expenditure of thought.

I view the work I've done related to statistics and economics as, roughly speaking, how to do something without having to do everything.

In science, we take large numbers of disparate facts and reduce them to see patterns. We use the patterns to reduce the amount of information. It's the reason we name species and genera and families in biology. It's also the reason we have names for certain types of geological features and so on in other fields.

In the first stage of insight-building, all that researchers can do is observe phenomena. Second, they classify the phenomena in a way that helps them simplify the apparent complexities of the world so they can ignore the meaningless differences and draw connections between the things that really seem to matter. Third, based on the classification system, they propose a theory. The theory is a statement of what causes what and why, and under what circumstances.