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--- data_analysis:probability_distributions [2023/02/25 16:27]
prgram [how?]
+++ data_analysis:probability_distributions [2023/02/25 18:23]
prgram [Geometric]
@@ Line 24: / Line 24: @@
 ==== Negative Binomial ====
 probability of the number of failures $r$ before observing $k$ successes in a sequence of independent and identically distributed Bernoulli trials.
+실패 r번, 성공 k번
+** 실패횟수에 초점 **
 $X \sim \text{NegBin}(k, p)$ or $X \sim \text{NegBin}(r, p)$, depending on the parameterization used. The two parameterizations are related by the identity $r = k - 1$.
-$$P(X = k) = {k+r-1 \choose k} p^k (1-p)^r$$
+$$P(X = k) = {k+r-1 \choose r} p^k (1-p)^r$$
 where $X$ is the random variable representing the number of trials until the $k$th success is observed, $p$ is the probability of success in a single trial, and $r$ is the number of failures before observing the $k$th success.
 === how? ===
-y번실험 시도에 x번 성공 -> y-1번째까지 x-1번 성공 & y번째 성공
+** 성공횟수에 초점**
-$$P(Y=y) = {y-1 \choose x-1} p^{x-1} (1-p)^{y-x} p $$
+m번실험 시도에 n번 성공 -> m-1번째까지 n-1번 성공 & m번째 성공
-$x=r$ (실패횟수) -> $y=r+k$ -> $ y-k = k $
+$$P(Y=n) = {m-1 \choose n-1} p^{n-1} (1-p)^{m-n} p $$
+$n=k$ (성공횟수) -> $m=r+k$ -> $ m-n = r $
+$ {k+r-1 \choose r} = {k+r-1 \choose k-1} $
 === example ===
 For example, the negative binomial distribution can be used to model the number of phone calls a telemarketer must make before getting a fixed number of sales, the number of defective products produced before a certain number of acceptable products are produced, or the number of attempts required to solve a particular puzzle or problem. The negative binomial distribution is also used in some areas of biology to model the distribution of offspring from a single parent in a population.
+==== Geometric ====
+Negative Binomial에서 k=1 일때 -> 성공할 때까지의 실험회수 (r=x-1)
+$$P(X = x) = p(1-p)^{x-1}$$
+==== Poisson ====
 ===== Continuous =====