When discussing the results of a particular experiment, typically you'll find scientists and the media talking about bias. Bias is an error in the results an experiment (usually because of the design) that favor one result or explanation. Bias in the scientific sense is different from personal preference. Bias can be intentional or unintentional when performing an experiment, sometimes it can't be completely avoided. There are different kinds of bias in scientific sense:
- This happens when the samples in an experiment (whatever they may be, usually people) are not typical of the overall population being sampled
- Example: sampling peoples' attitudes of gun control in Texas but only interviewing people who live in Dallas and nowhere else.
2. Researcher bias
- When the researcher(s) want a particular result to arise out of the experiment and affect
- Example: religious researchers who want to attribute a particular phenomena to God instead of assuming another, most-likely more plausible explanation
3. Personal bias
- In studies involving people, this usually happens when the people in the study know what the experiment is trying to explain and then try to affect the result in a particular direction. This is why most experiments are ran blind study.
4. Sample size bias
- This is a form of selection bias in which the sample size is small (could be for many reasons and sometimes not on purpose) and results in skewed results.