# A First Course in Probability

Book by Sheldon Ross

Scott Mueller (lvl 19)
Chapter 2

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Inclusion-exclusion identity

Front

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## Cards(6)

Chapter 2

(1 card)

Inclusion-exclusion identity

Front

\begin{aligned}P\left(\bigcup_{i=1}^n A_i\right) &= \sum_{i=1}^n P(A_i) - \underset{i<j}{\sum\sum} P(A_iA_j)\\&+ \underset{i<j<k}{\sum\sum\sum} P(A_iA_jA_k)\\&- \ldots + (-1)^{n+1}P(A_1\cdots A_n)\end{aligned}

Back

Chapter 3

(1 card)

Gambler's ruin problem

Front

Probability of winning is

$P_i = \begin{cases}\frac{1 - (q/p)^i}{1 - (q/p)^N} & \text{if } p \neq \frac12\\\frac{i}{N} & \text{if } p = \frac12\end{cases}$

when starting with $$i$$ out of $$N$$ units and winning each round with probability $$p$$ ($$q = 1 - p$$).

Back

Chapter 4

(4 cards)

Expected value and variance of a Binomial random variable

Front

\begin{aligned}\mu &= n \cdot p\\\sigma^2 &= n \cdot p \cdot (1 - p)\end{aligned}

Back

$$i \cdot {n \choose i}$$

Front

$$n \cdot {n - 1 \choose i - 1}$$

Back

Expected value and variance of a Poisson random variable

Front

\begin{aligned}\mu &= \lambda\\\sigma^2 &= \lambda\end{aligned}

Back

Poisson paradigm (aka law of rare events)

Front

If $$n$$ is large and $$P(\text{event})$$ is small, the number of events is approximately modeled by the Poisson distribution where $$\lambda = \sum_{j=1}^n p_j$$.

Back