Bias
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Bias means that a person prefers an idea and possibly does not give equal chance to a different idea. Bias can be influenced by a number of factors, such as popularity.
For instance, a newspaper might be biased towards a particular political party because their owner or employees share that party's political beliefs. Because of this bias, the newspaper might print more positive stories about that party and more negative articles about other parties.
Examples
changePublishing
changeBias in writing can also involve using slang or bad words to refer to groups of people or things. For example, an article that uses the word "murder-cycles" instead of "motorcycles" is showing a bias against motorcycles.
Another form of bias is using words or phrasing that make wide assumptions about races or groups of people. This is true even when the assumptions are positive (like "All Chinese people are good at math").
Media
changeBias in an article or editorial would show one point of view, using selected facts and quotes to support that point of view. Facts or opinions that do not support the point of view in a biased article would be excluded. For example, an article biased toward riding a motorcycle would show facts about their good gas mileage, fun, and agility.[clarification needed] An article biased against motorcycle riding would show facts about risk of injury and noise, and ignore positive facts about motorcycles.
An article biased against guns would show only facts and information that support the author's position. It might list suicides, school shootings, accidental shootings, and other facts showing guns in a negative way. An article biased for guns should show only information that supports the author's position. It might discuss "lives saved by guns", numbers about crimes prevented by civilian gun use, and other facts and data that put gun ownership and guns in a good light.
Measurement
changeBias also means mistakes in measurement. For example, a person may measure the height of another person wearing shoes. The shoes make the height more than the same person without shoes. If the extra height of the shoes (extra bias) was not explained, someone might think that the person had been measured without shoes on. Data with extra parts not explained is called biased data.
