- Random: when individual outcomes are uncertain but there is nonetheless a regular distribution of outcomes in a large number of repetitions
- Probability: the proportions of times an outcome would occur in a random phenomenon in a very long series of repetition, the long term relative frequency
- Independence: the outcome of one trial does not influence the outcome of any other
- Sample space S: is the set of all possible outcomes in a random phenomenon
- Event: any outcome or set of outcomes of a random phenomenon, the subset of the sample space
- Probability model: a mathematical description of a random phenomenon consisting of two parts- sample space S and a way of assigning probabilities to events
- Tree diagram: a diagram in which lines branch out from a central pointor stem without forming any closed loops
- Replacement: sampling when you return each subject back into the sample after drawing it so that every subject has the same probability of being chosen each time
- Union: in the event {A U B} or “A union B” , it is the set of all outcomes that are either in A or B
- Empty event: the event that has no outcomes in it, of any collection of events it is the event that at least one of the collection occurs
- Intersect: in the event “A intersect B”, it is the set of outcomes that are in both A and B, of any collection of events it is the event that all of the events occur
- Venn diagram: a picture that shows the sample space S as a rectangular area and events as areas within S
- Independent: when knowing that one event occurs does not change the probability that the other occurs
- Conditional probability: gives the probability of one event under the condition that we know another event (like the probability the next card dealt will be an ace and the knowledge that there exactly one of the four cards is an ace)
- Disjoint: when two events are mutually exclusive
- Complement: of an event A, it contains all outcomes that are not in A