Review an experimental design to determine possible sources of bias or error, state alternative explanations, and identify questions for further investigation 0807.Inq.4

Links verified 9/21/2014

1. Bias - systematic, or biased, errors are errors which consistently yield results either higher or lower than the correct measurement
2. 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)
3. Blind Experiment - ways top avoid conscious or unconscious bias
4. Common Mistakes in Applying the Scientific Method - discussion regarding experimenter bias
5. Confirmation Bias In Science: How To Avoid It - regarding one of the most common arguments against a scientific finding
6. Experimenter Bias - includes ways to avoid bias in an experiment [This expired link is available through the Wayback Machine Internet Archive. If the page doesn't load quickly click on Impatient? at the bottom right of the page.]
7. Experimenter's Bias - Wikipedia entry on the subject
8. Experimenter's Bias - Wikipedia entry
9. How Science works: Errors - Explains random and zero errors, parallax, and anomalous results.
10. 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.
11. Research Bias - a process where the scientists performing the research influence the results, in order to portray a certain outcome
12. Sampling Error - the deviation of the selected sample from the true characteristics, traits, behaviors, qualities or figures of the entire population
13. 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
14. Systematic Error - a type of error that deviates by a fixed amount from the true value of measurement

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