Learning Goal
Part of: Calculate expected values and use them to solve problems — 4 of 4 cluster items
Develop an empirical probability distribution
**HSS.MD.A.4**: (+) Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value. For example, find a current data distribution on the number of TV sets per household in the United States, and calculate the expected number of sets per household. How many TV sets would you expect to find in 100 randomly selected households?
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HSS.MD.A.4: (+) Develop a probability distribution for a random variable defined for a sample space in which probabilities are assigned empirically; find the expected value. For example, find a current data distribution on the number of TV sets per household in the United States, and calculate the expected number of sets per household. How many TV sets would you expect to find in 100 randomly selected households?
What you'll learn
- Develop an empirical probability distribution by converting observed counts or frequencies into relative-frequency probabilities
- Verify the developed distribution sums to approximately 1 (handling rounding) and graph it as a probability histogram
- Compute the expected value of an empirically developed distribution, including handling an open-ended category with a stated representative value
- Scale an expected value to a population total using n*E(X)
- Explain how an empirical distribution differs from a theoretical one and how sample size and representativeness affect the quality of the estimate
Slides
Interactive presentations perfect for visual learners • 2 slide decks
Slide Video
Watch narrated slides play like a video lesson • Narrated slide playback