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