Availability bias refers to the tendency to generalize from a small sample or a single event. Which label corresponds to this bias?

Availability bias refers to the tendency to generalize from a small sample or a single event. Which label corresponds to this bias?

• A. The tendency to generalize from a small sample or a single event
• B. The tendency to overestimate rare events
• C. The tendency to anchor on initial information
• D. The tendency to ignore base rates

Answer: (A)

Availability bias shows up when judgments are shaped by how easily examples come to mind. If a few memorable events or a single dramatic incident are what you recall, you’re likely to generalize from that small sample to broader patterns in the world. That tendency—drawing broad conclusions from a limited set of experiences or information you can easily recall—is exactly what this label describes. For example, after hearing about a few airline accidents, you might conclude that flying is extremely dangerous, even if statistics don’t support that view. The other options describe different biases—overestimating rare events is a consequence of availability in some cases, but the label here emphasizes generalizing from a small sample; anchoring means sticking to initial information; ignoring base rates means failing to consider overall statistical data.

Availability bias shows up when judgments are shaped by how easily examples come to mind. If a few memorable events or a single dramatic incident are what you recall, you’re likely to generalize from that small sample to broader patterns in the world. That tendency—drawing broad conclusions from a limited set of experiences or information you can easily recall—is exactly what this label describes. For example, after hearing about a few airline accidents, you might conclude that flying is extremely dangerous, even if statistics don’t support that view. The other options describe different biases—overestimating rare events is a consequence of availability in some cases, but the label here emphasizes generalizing from a small sample; anchoring means sticking to initial information; ignoring base rates means failing to consider overall statistical data.