Identify a faulty interpretation of data that is due to bias or experimental error SPI 0607.Inq.5

Links verified 5/16/2024

1. Bias and Random Error - Random error corresponds to imprecision, and bias to inaccuracy. This site has a diagram that will attempt to differentiate between imprecision and inaccuracy
2. Bias and Sources of Error - Learn how scientists identify and minimize bias and sources of error to produce accurate results
3. 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)
4. Data Analysis and Interpretation - Did you know that scientists don't always agree on what data mean? Different scientists can look at the same set of data and come up with different explanations for it, and disagreement among scientists doesn't point to bad science.
5. How Science works: Errors - Explains random and zero errors, parallax, and anomalous results.
6. 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.
7. Practices of Science: Scientific Error - identifying types of error
8. Random vs. Systematic Error - definition and examples
9. Statistics with Crayons - (4:16) a YouTube video about bias and random error with Hans and Hera

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