W1.L4. Probability & Distribution
| Probability
$ P(E) \in \mathbb{R} $
$ P(E) \geqslant 0 $
$ P(\Omega) = 1 $
$ P(E_1 \cup E_2 \cup \ ... \ ) = \sum_{i=1}^{\infty} P(E_i) $ when a sequence of mutually exclusive
If $ A \subseteq B$ then $P(A) \leqslant P(B) $
$ P(\varnothing) = 0 $
$ 0 \leqslant P(E) \leqslant 1 $
$ P(A \cup B)=P(A) + P(B) - P(A \sqcap B) $
$ P(E^C) = 1 - P(E) $
| Conditional Probability
B 라는 조건이 참인 경우, A 의 확률
$$ P(A \mid B) = \frac{P(A \cup B)}{P(B)} $$
$$ P(B \mid A) = \frac{P(A \mid B) \cdot P(B)}{P(A)} $$
$$ P(A) = \sum_{n} P(A \mid B_n) \cdot P(B_n) $$
Whole conditional probability & priors
| Probability Distribution
어떠한 Event 가 발생한다는 것을 특정 Value 로 mapping / assign 하는 것!
A Function mapping an event to a probability
Example
$$f(x) = \frac{1}{\sqrt{2\pi}} e^{-\frac{1}{2}x^2} $$
$ x $ : Event의 한 종류 ... $ x=3 $, $ x=5 $, ...
Representatives
Reference
문일철 교수님 강의
https://www.youtube.com/watch?v=z62VosBB2o8&list=PLbhbGI_ppZISMV4tAWHlytBqNq1-lb8bz&index=5