随笔分类 -  基本概率分布基础

摘要：PDF versionPDF & CDFThe probability density function is $$f(x; \mu, \sigma) = {1\over\sqrt{2\pi}\sigma}e^{-{1\over2}{(x-\mu)^2\over\sigma^2}}$$ The cu... 阅读全文

摘要：PDF versionPDF & CDFThe probability density function of the uniform distribution is $$f(x; \alpha, \beta) = \begin{cases}{1\over\beta-\alpha} & \mbox{... 阅读全文

摘要：PDF versionPDF & CDFThe exponential probability density function (PDF) is $$f(x; \lambda) = \begin{cases}\lambda e^{-\lambda x} & x\geq0\\ 0 & x 10) ... 阅读全文

摘要：PDF versionPMFSuppose that a sample of size $n$ is to be chosen randomly (without replacement) from an urn containing $N$ balls, of which $m$ are whit... 阅读全文

摘要：PDF versionPMFSuppose there is a sequence of independent Bernoulli trials, each trial having two potential outcomes called "success" and "failure". In... 阅读全文

摘要：PDF versionPMFSuppose that independent trials, each having a probability $p$, $0 0){+ p = (5/6) ^ n+ if (p < 0.05) break+ n = n + 1+ }n# [1] 17... 阅读全文

摘要：PDF versionPMFA discrete random variable $X$ is said to have a Poisson distribution with parameter $\lambda > 0$, if the probability mass function of ... 阅读全文

摘要：PDF下载链接PMFIf the random variable $X$ follows the binomial distribution with parameters $n$ and $p$, we write $X \sim B(n, p)$. The probability of gett... 阅读全文