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This page was last edited on 19 December 2024, at 01:32 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
[3] [4] [5] For example, in studies of risk factors for breast cancer, women who have had the disease may search their memories more thoroughly than members of the unaffected control group for possible causes of their cancer. Those in the case group (those with breast cancer) may be able to recall a greater number of potential risk factors they ...
Research on attribution biases is founded in attribution theory, which was proposed to explain why and how people create meaning about others' and their own behavior.This theory focuses on identifying how an observer uses information in his/her social environment in order to create a causal explanation for events.
For example, if the mean height in a population of 21-year-old men is 1.75 meters, and one randomly chosen man is 1.80 meters tall, then the "error" is 0.05 meters; if the randomly chosen man is 1.70 meters tall, then the "error" is −0.05 meters.
This page was last edited on 1 December 2021, at 13:57 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may apply.
Selection bias refers to the problem that, at pre-test, differences between groups exist that may interact with the independent variable and thus be 'responsible' for the observed outcome.
Unbiased rendering in computer graphics refers to techniques that avoid systematic errors, or biases, in the radiance approximation of an image. This term specifically relates to statistical bias, not subjective bias. Unbiased rendering aims to replicate real-world lighting and shading as accurately as possible without shortcuts.