Standard(s):
[MA2019] REG-7 (7) 14 : 14. Define and develop a probability model, including models that may or may not be uniform, where uniform models assign equal probability to all outcomes and non-uniform models involve events that are not equally likely.
a. Collect and use data to predict probabilities of events.
b. Compare probabilities from a model to observed frequencies, explaining possible sources of discrepancy.
[DLIT] (7) 33 : 27) Identify data needed to create a model or simulation of a given event.
Examples: When creating a random name generator, the program needs access to a list of possible names.
[MA2019] ACC-7 (7) 30 : 30. Define and develop a probability model, including models that may or may not be uniform, where uniform models assign equal probability to all outcomes and non-uniform models involve events that are not equally likely.
a. Collect and use data to predict probabilities of events.
b. Compare probabilities from a model to observe frequencies, explaining possible sources of discrepancy. [Grade 7, 14]