| A | B |
|---|
| Basic Counting Principle | If event M can occur in M ways and is followed by an event N that can occur in N ways, then the event M followed by the event N can occur in M*N ways. |
| Binomial Experiments | A problem that can be solved using binomial expansion. |
| Circular Permutation | A circular arrangement of objects in a certain order. |
| Combination | An arrangement of objects where the order is not considered. |
| Combinatorics | The investigation of the different possibilities for the arrangement of objects |
| Complements | Two events are compliments if and only if the sum of their probabilities is 1. |
| Conditional Probability | The probability of an event under the condition that some preceding event has occurred. |
| Dependent event | Events that have no effect on each other. |
| Experimental Probability | A probability determined by performing tests or experiments and observing outcomes. |
| Failure | Any outcome other than the desired outcome event |
| Inclusive event | Two events whose outcomes may be the same. |
| Independent event | Events that do not affect each other. |
| Mutually exclusive | Two events whose outcomes can never be the same. |
| Odds | The ratio of probability of the success of an event to the probability of a failure of an event. |
| Permutation | The arrangement of objects in a certain order. |
| Permutation with repetition | The arrangement of objects in a certain order in which some of the objects are alike. |
| Reduced sample space | The subset of a sample space that contains only those outcomes that satisfy a given condition. |
| Sample Space | The set of all possible outcomes of an event. |
| Simulation | A technique used to model probability experiments for real world applications. |
| Success | The desired outcome of an event. |
| Theoretical Probability | Probability determined using mathematical methods to model outcomes of a given situation. |
| Tree Diagram | A diagram used to show the total number of possible outcomes in an event. |
