commit c9f51d214913638ec2c86f40cd7ede6cc6aabc87 parent 3d921d5905db07ed75ab74027d913c394785688b Author: Andrew <andrewlaack1@gmail.com> Date: Wed, 17 Jul 2024 07:57:07 -0500 Some notes Diffstat:
| M | ProbabilityMassFunction.md | | | 6 | ++++++ |
1 file changed, 6 insertions(+), 0 deletions(-)
diff --git a/ProbabilityMassFunction.md b/ProbabilityMassFunction.md @@ -26,6 +26,12 @@ In the below example assume each connection is the function defined by the Rando With proper notation (and assuming random variable X) we can state the above as $P_X(x) = P(A), \space P_X(y) = P(B)+P(C)$ etc. +## Expected Value + +The expected value of a PMF is the most probable output. This is calculated by summing the probabilities of each output multiplied by the output value. This will be the 'middle' of the sample space. + +This is denoted by the function E[] where the inside is the random variable that is being predicted upon. + ## Geometric The geometric PMF is a specific PMF where every subsequent output decreases by a given percent each time creating a form of poisson distribution.