it minimizes sources of bias in the data
bias
Science should not be bias, it either is or it isn't. If one is basing their study on a bias, they could miss or dismiss certain results because of their beliefs rather than facts. It would be faulty science.
The answer is Random Sample
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.
Apex: Most social studies sources contain bias
it minimizes sources of bias in the data
Some Bias
some amount of bias
bias is the set of preferences or prejudices a writer has about a subject
some amount of bias
Bias occurs when a writer intentionally omits information that weakens his or her argument.
Corroborating sources in political science allows researchers to verify information, strengthen the credibility of their findings, and support more robust and accurate analysis of political phenomena. By comparing information from multiple sources, researchers can reduce bias and ensure the reliability of their conclusions.
Cross-checking sources against other evidence. However, there's no 'patent recipe' for dealing with problems of bias in sources.
bias
it is a good answer or choice
The Bias rule recognizes that all sources have inherent biases or perspectives that can influence the information they present. It emphasizes the need to critically analyze sources and consider their potential biases when evaluating their credibility and reliability.