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[工科概率论] 各种连续型分布

均匀分布#

XU(a,b)X \sim U(a, b)f(x)={1ba,axb0,otherwisef(x) = \begin{cases} \frac{1}{b-a}, & a \le x \le b \\ 0, & \text{otherwise} \end{cases}F(x)={0,x<axaba,axb1,x>bF(x) = \begin{cases} 0, & x < a \\ \frac{x-a}{b-a}, & a \le x \le b \\ 1, & x > b \end{cases}E(X)=a+b2E(X) = \frac{a+b}{2}D(X)=(ba)212D(X) = \frac{(b-a)^2}{12}

指数分布#

XE(λ)X \sim E(\lambda)

λ\lambda称为指数分布的参数,λ>0\lambda > 0

f(x)={λeλx,x00,x<0f(x) = \begin{cases} \lambda e^{-\lambda x}, & x \ge 0 \\ 0, & x < 0 \end{cases}F(x)={1eλx,x00,x<0F(x) = \begin{cases} 1 - e^{-\lambda x}, & x \ge 0 \\ 0, & x < 0 \end{cases}E(X)=1λE(X) = \frac{1}{\lambda}D(X)=1λ2D(X) = \frac{1}{\lambda^2}

正态分布#

XN(μ,σ2)X \sim N(\mu, \sigma^2)f(x)=12πσe(xμ)22σ2\large f(x) = \frac{1}{\sqrt{2\pi} \sigma} e^{\large -\frac{(x-\mu)^2}{2\sigma^2}}

分布函数不考察,通过查表求值

E(X)=μE(X) = \muD(X)=σ2D(X) = \sigma^2

标准正态分布#

XN(0,1)X \sim N(0, 1)
[工科概率论] 各种连续型分布
https://a1kari8.github.io/posts/probability_theory/continuous_distribution/
作者
A1kari8
发布于
2025-11-23
许可协议
CC BY-NC-SA 4.0