Last active
February 16, 2017 12:17
-
-
Save andykuszyk/e3810f94f7af24118c4b1578768198c5 to your computer and use it in GitHub Desktop.
Probabilities
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# Probabilities\n", | |
"\n", | |
"$X$ and $Y$ are events such that $X,Y \\in A$ where $A$ is the set of events.\n", | |
"\n", | |
"## Probability of an event\n", | |
"The probability of an event $X$ in an event space $A$: $P(X) = count(X) / count(A)$\n", | |
"\n", | |
"## Probability of two events\n", | |
"Probability of event $X$ and event $Y$ in event space $A$: $P(X and Y) = count(X and Y) / count(A)$\n", | |
"\n", | |
"## Conditional probability\n", | |
"Probability of $X$ given $Y$: \n", | |
"$$ P(X|Y) = \\frac{P(X and Y)}{P(Y)} $$\n", | |
"\n", | |
"## Propability of independant events\n", | |
"Probability of $X$ and $Y$ when they are independent: $ P(XY) = P(X) + P(Y)$\n", | |
"\n", | |
"## Probability of dependent events\n", | |
"Probability of $X$ and $Y$ when they are dependent: $ P(XY) = P(X) \\times P(Y) $\n", | |
"\n", | |
"## Bayes theorem\n", | |
"$$ P(X|Y) = \\frac{P(Y|X)P(X)}{P(Y)}$$" | |
] | |
} | |
], | |
"metadata": { | |
"anaconda-cloud": {}, | |
"kernelspec": { | |
"display_name": "Python [default]", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.5.2" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 1 | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment