Difference between revisions of "Distributions"
(→General Symbols/Definitions) |
(→General Symbols/Definitions) |
||
| Line 4: | Line 4: | ||
Distributions give a general description of what the probabilities and events look like. The sample space, which is represented like <math>\Omega</math>, represents the set of all possible outcomes. For example, <math>\Omega =</math> {<math>1, 2, 3, 4, 5, 6</math>} would represent the sample space of rolling a die. | Distributions give a general description of what the probabilities and events look like. The sample space, which is represented like <math>\Omega</math>, represents the set of all possible outcomes. For example, <math>\Omega =</math> {<math>1, 2, 3, 4, 5, 6</math>} would represent the sample space of rolling a die. | ||
| − | The difference | + | The difference between Discrete and Continuous, is that discrete has a finite possible number of outcomes, and continuous |
Revision as of 20:53, 8 July 2024
Probability distribution is a function that gives the outcome of an event, to their corresponding probabilities. For example, in rolling a fair dice, with 
sides, 
would be 
.
General Symbols/Definitions
Distributions give a general description of what the probabilities and events look like. The sample space, which is represented like 
, represents the set of all possible outcomes. For example, 
{
} would represent the sample space of rolling a die.
The difference between Discrete and Continuous, is that discrete has a finite possible number of outcomes, and continuous
