Biases of data selection

Biases of data selection (summarized alphabetically in Table 7-1) enable pattern recognition by means of selecting some pieces of information and discarding others in order to establish a recognizable pattern. These biases differ from each other primarily in the (usually unconscious) principle by which we make these selections. 

Prototyping is a tendency to automatically select data that fit a mental model of the situation. The successful practice of medicine has its roots in highly refined prototyping, which is a form of pattern recognition. A clinician has amassed years of experience with numerous illnesses and stored this experience as mental models of disease states. When she sees a patient, relevant models jump to 

Putting too much weight, or anchoring. on the first information received or on a specific piece of information over alt others allowing the initial or preferred information to anchor subsequent judgments. 

Seeking and highlighting data that confirm your preconceptions, views, expectations, fears, or desires. 

Regarding and presenting strongly held values as facts instead of personai values. 

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