Chapter 11: Thinking

Algorithms: lead to right answer but time and resource consumming

Heuristics: economical rule of thumb that works well enough often enough
     Representativeness heuristic: infer that an object shares the characteristics of its category
          Basis for stereotypes
          Ignore base rates: gambler's fallacy
          Ignore sample size: law of small numbers: incorrectly assume that small sample is as representative as a large one
          Useful for categorization and implicit learning.

     Simulation heuristic: how easy it is to imagine an alternative outcome to an event
          Undoing heuristic: mainly based on downhill changes that normalize the story
               Focus rule
          Hindsight bias: what just happened is perceived as predictable, very likely to have happened
               Easiest to imagine
               Makes other outcome seem less likely