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Bias in science is anything that would skew either the collection or interpretation of data. Examples of bias include non-random sampling which excludes a certain age group or ethnicity, observing only those specimens that appear to fit the hypothesis, and running inappropriate statistical tests to support a conclusion.

Bias is extremely difficult to avoid entirely in science - there is never a perfect representative sampling and the scientist will always have some degree of bias towards his/her pet hypothesis. However, egregious bias can be removed through a careful experimental design and rigorous ethical adherence to the procedure. It also helps to have other scientists read through the design and the protocol to point out any unintentional biases or potential problems, and you should be current with the published literature to identify confounders and other issues that other scientists working in this field have already identified.

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