Probability model

Definition

A probability model is a mathematical representation of a random phenomenon. It consists of a sample space, events within the sample space, and probabilities associated with each event.

5 Must Know Facts For Your Next Test

1. A probability model includes a sample space (S), which is the set of all possible outcomes.
2. The sum of probabilities for all possible outcomes in a sample space is 1.
3. Events are subsets of the sample space to which probabilities are assigned.
4. A discrete probability model deals with countable outcomes while a continuous one deals with uncountable outcomes.
5. In conditional probability models, the probability of an event depends on the occurrence of another event.

Review Questions

• What components make up a probability model?
• How do you differentiate between discrete and continuous probability models?
• What ensures that the total probability in a model sums up to 1?

Related terms

Sample Space: The set of all possible outcomes in a probability experiment.

Event: A subset of the sample space; it can consist of one or more outcomes.

Conditional Probability: The likelihood of an event occurring given that another event has already occurred, denoted as $P(A|B)$.