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binomial_distribution [2019/11/04 15:13] hkimscilbinomial_distribution [2020/11/27 19:42] (current) hkimscil
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 ====== Binomial Distribution ====== ====== Binomial Distribution ======
 +  - 1번의 시행에서 특정 사건 A가 발생할 확률을 p라고 하면
 +  - n번의 (독립적인) 시행에서 사건 A가 발생할 때의 확률 분포를
 +  - 이항확률분포라고 한다.
  
 \begin{eqnarray*} \begin{eqnarray*}
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 **The number of successes in n independent Bernoulli trials has a binomial distribution.**  **The number of successes in n independent Bernoulli trials has a binomial distribution.** 
  
-independent Bernoulli trials +이는 번의 독립적인 Bernoulli trials 로 볼 수 있다.
   * There are n independent trials   * There are n independent trials
   * Each trial can result in one of two possible outcomes, labelled success and failure.   * Each trial can result in one of two possible outcomes, labelled success and failure.
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   * P(success) = p,    * P(success) = p, 
   * P(failure) = 1-p   * P(failure) = 1-p
 +
 +일반적으로 binomial distribution은 아래와 같이 계산된다. 
 +
 +\begin{align*}
 +P(X=x) & = _{n}C_{x} \cdot p^{x} \cdot (1-p)^{n-x}, \;\; \text{for} \;\; x = 0, 1, 2, . . ., n. \\
 +\text{or } & \\
 +P(X=x) & = {{n} \choose {x}} \cdot p^{x} \cdot (1-p)^{n-x}, \;\; \text{for} \;\; x = 0, 1, 2, . . ., n. \\
 +\end{align*}
 +
 +A balanced dice is rolled 3 times. What is probability a 5 comes up exactly twice?
 +
 +p = 1/6
 +n = 3
 +x = 2
  
 \begin{eqnarray*} \begin{eqnarray*}
-P(X=x) = _{n}C_{x} \cdot p^{x} \cdot (1-p)^{n-x}\;\\text{for} \;\; x = 0, 1, 2, . ., n. \\+P(X=2{{3} \choose {2}} \left(\frac{1}{6}\right)^{2} \left(\frac{5}{6}\right)^{3-2} \\ 
 +0.0694
 \end{eqnarray*} \end{eqnarray*}
  
 +<code>
 +> dbinom(2, 3, 1/6)
 +[1] 0.06944444
 +
 +</code>
  
  
binomial_distribution.1572847993.txt.gz · Last modified: 2019/11/04 15:13 by hkimscil

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