This chapter talks much about how to represent data precisely in graphics. The distortion of data with bad design leads readers toward wrong precision.
The Lie Factor can be used to measuring the deformation in data design. He compared the "data variation" and the "design variation". discussed the importance of using multiple dimension and context in the data design. The author told people how to be a good designer, and at the same time, you can learn how to be a tricky designer.
Here is a conclusion.
The representation of numbers, as physically measured on the surface of the graphic itself, should be directly proportional to the numerical quantities represented.
clear, detailed, and thorough labeling should be used to defeat graphical distortion and ambiguity. write our explanations of the data on the graphic itself. Label important events in the data.
Show data variation, not design variation.
In time-series displays of money, deflated and standardized units of monetary measurement are nearly always better than nominal units.
The number of information-carrying (variable) dimensions depicted should not exceed the number of dimensions in the data.
Graphics must not quote data out of context.
引自 Graphical Integrity
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