Richard Nisbett's Mindware: Tools for Smart Thinking should be required reading for every university student (or anyone else who wants to make fewer reasoning errors). The book consists of an eclectic but extremely practical collection of "tools for smart thinking", covering concepts as varied as the sunk cost fallacy, confirmation bias, the law of large numbers, the endowment effect, and multiple regression analysis, among many others.
Read moreDo tooltips reduce the need for precision in graphs?
In many modern data visualization software applications, users can hover their cursor or finger over any bar, dot, box, line, etc. to see the exact, textual value(s) of each element. Since this allows users to see exact values whenever they need to know them, does this mean that graph designers no longer need to worry about how precisely values in their graphs can be estimated visually (i.e., without seeing a tooltip)?
Read moreAvoiding quantitative scales that make graphs hard to read
Every so often, I come across a graph with a quantitative scale that's confusing or unnecessarily difficult to use when visually estimating values in the graph. In this post, I propose simple guidelines for data visualization software developers to follow to ensure that the default quantitative scales that their products generate make it easy for audiences to "eyeball" values in the graph easily and accurately.
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