What is a consequence of representative bias in decision making?

The consequence of representative bias in decision-making is that individuals develop a view based solely on new information or small sample sizes. This bias occurs when people judge the probability of an event based on how much it resembles existing categories or their preconceived notions, rather than considering all relevant data. As a result, they may place too much emphasis on specific instances or analogies drawn from limited experiences or information, leading to skewed or inaccurate conclusions.

In this context, decision-makers who are influenced by representative bias might focus on recent or vivid examples and let those inform their expectations, ignoring broader statistical realities or larger data samples that could provide a more reliable picture. This reliance on limited data can ultimately lead to poor decision-making because it fails to account for the complete scenario and can reinforce incorrect assumptions based on a narrow perspective.

This is distinct from the other choices, which imply different cognitive biases or decision-making issues. The tendency to make decisions solely based on past success suggests over-reliance on historical performance without considering potential changes in the environment. Reliance on comprehensive data analysis would indicate an informed approach, contrary to the representative bias. Valuing base rate over new data is related, but focuses on a different aspect of decision-making, where individuals fail to integrate new