MA19.7.14
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.
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.
Unpacked Content
UP:MA19.7.14
Vocabulary
- Probability model
- Uniform model
- non-uniform model
- observed frequencies
Knowledge
Students know:
- the probability of any single event can be expressed using terminology like impossible, unlikely, likely, or certain or as a number between 0 and 1, inclusive, with numbers closer to 1 indicating greater likelihood.
- A probability model is a visual display of the sample space and each corresponding probability
- probability models can be used to find the probability of events.
- A uniform probability model has equally likely probabilities.
- Sample space and related probabilities should be used to determine an appropriate probability model for a random circumstance.
Skills
Students are able to:
- make predictions before conducting probability experiments, run trials of the experiment, and refine their conjectures as they run additional trials.
- Collect data on the chance process that produces an event.
- Use a developed probability model to find probabilities of events.
- Compare probabilities from a model to observed frequencies
- Develop a probability model (which may not be uniform) by observing frequencies in data generated from a chance process.
Understanding
Students understand that:
- long-run frequencies tend to approximate theoretical probability.
- predictions are reasonable estimates and not exact measures.
