Review an experimental design to determine possible sources of bias or error, state alternative explanations, and identify questions for further investigation 0707.Inq.4
Links verified on 6/24/2014
- Bias - systematic, or biased, errors are errors which consistently yield results either higher or lower than the correct measurement
- Biased Sample - also known as: Biased Statistics, Loaded Sample, Prejudiced Statistics, Prejudiced Sample, Loaded Statistics, Biased Induction, Biased Generalization (3 good examples at the bottom of the page)
- Experimenter's Bias - Wikipedia entry
- How Science works: Errors - Explains random and zero errors, parallax, and anomalous results.
- How Science works: Reliable evidence and Valid evidence - Explains the meaning of 'data' and 'evidence', 'reliability' and 'validity', 'secondary' evidence, with examples for you to discuss.
- Research Bias - a process where the scientists performing the research influence the results, in order to portray a certain outcome
- Sampling Error - the deviation of the selected sample from the true characteristics, traits, behaviors, qualities or figures of the entire population
- Sources of Error - [37 page .pdf document] a framework for identifying potential sources and impact of distortion in observational studies, with approaches to maintaining validity
- Systematic Error - a type of error that deviates by a fixed amount from the true value of measurement
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