(1) Schweser cognitive errors says: representativeness bias can take several forms. New informaiton is evaluated based on past classification or experience without more thorough analysis. - In base rate neglect new information is given too much importance. - In sample-size neglect new information is also overweighted and taken as too representative. (2) Schweser Analyst biases in research says: - Representative bias: one in which the analyst inaccurately extrapolates past data into the future (e.g. classifying firm as a growth firm based on previous high growth without considering variables affecting firm’s future). Question: Representative bias in (1) places too much importance on new information but (2) puts more information on past data, can someone please explain this?
it’s a cognitive error (belief perseverance) where you can either :
> (non comprehensively) “representing” new information based on past representation / experience (base-rate neglet). You essentially classify new information based on your past experience only even though the new information doesn’t properly fit;
> taking investment decisions based on a non-representative sample but the sample you have does sound (wrongly) sufficient to allow you to undertake your decision.