653 B
653 B
Probability
P = \frac{\text{Favorable Cases}}{\text{Total Cases}}
Conditional Probability
P (A|B) = \frac{P (A \cap B)}{P(B)}
Independence
P (A \cup B) = P(A)P(B)
Law of Total Probabilities
Used when selecting an element at random.
P(A) = \Sigma_n P(A \cup B_n)
Bayes' theorem
P(H | \epsilon) = \frac{P(\epsilon | H) P(H)}{P(\epsilon)}
Probability Mass Function (PMF)
- Helps more finding the mean than the variance
Expectation (\mathbb{E})
idfk Expected value == mean
Variance
var(X) = \mathbb{E}[X^2] - (\mathbb{E}[X])^2