Topic IV. Systematic and Statistical Uncertainty
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LEARNING GOALS
- B. CONCEPT ACQUISITION
- Statistical Uncertainty/Error: Differences between reality and our measurement on the basis of random imprecisions.
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EXAMPLES
- Cautionary Quotes: Mistakes, Misconceptions, & Misunderstandings
- Difficulty distinguishing degrees of statistical error or uncertainty
- "We can't say one instrument has more statistical uncertainty than the other, because everything has statistical uncertainty."
- Failing to Notice Possibility of Statistical Error
- "I know that everyone likes chocolate, because I asked three of my friends and all of them said they like chocolate."
- "Scientists ran a randomized controlled study with 30 people and four conditions, and the results were statistically significant, so we know the drug works."
LEARNING GOALS
- A. ATTITUDES
- Often our contact with reality is mediated by measurement and quantification. We need to be aware that every measurement comes with some degree of uncertainty.
- B. CONCEPT ACQUISITION
- Statistical Uncertainty/Error: Differences between reality and our measurement on the basis of random imprecisions.
- a. All measurements have a certain amount of variance, which are just differences between multiple measurements due to error and/or genuine variation in the sample. These differences will not all go in the same direction.
- b. Statistical uncertainty can be reduced by averaging a larger amount of data.
- C. CONCEPT APPLICATION
- Identify sources of measurement uncertainty/error that introduce statistical uncertainty/error, that introduce systematic uncertainty/error, and that introduce both.
- Suggest approaches to reducing or constraining measurement uncertainty (both statistical and systematic).
CLASS ELEMENTS
- Homework Questions
- One way to gather data about how people might respond to a product or idea is to conduct a “focus group,” in which several participants share their impressions in a group conversation. Based on the reading, why is or isn’t this a good way to obtain reliable information?