概率论第二、三章题目

2020,03,12

3、某工厂产品的不合格率为0.03,现要把产品装箱,若要以不小于0.9的概率保证每箱中至少有100件合格品,那么每箱至少应装多少件产品?

100 + x k 根据题意,假设有100+x件产品,其中有k件次品

k = 0 x C 100 + x k 0.0 3 k 0.9 7 100 + x k 0.9 \sum_{k=0}^{x}C_{100+x}^k0.03^k*0.97^{100+x-k}\geq0.9

便 ∵二项分布不方便计算,∴可以用泊松分布来近似求解

x ( 100 + x ) 0.03 3 λ = 3 ∵x不会很大,∴(100+x)*0.03\approx 3,∴λ=3

k = 0 x 3 k k ! e 3 0.9 有\sum_{k=0}^x\frac{3^k}{k!}e^{-3}\geq0.9

k 5 k大概是5的样子

4、 A 线 y = 2 x x 2 x A y t 设A为曲线y=2x-x^2与x轴所围成的封闭区域,在A中任取一点,求该点到y轴的距离 t 的分布函数及密度函数

t 0 P { x t } = 0 ①t\leq 0,P\{x\leq t\}=0

t 2 P { x t } = 1 ②t\geq 2,P\{x\leq t\}=1

0 < t < 2 P { x t } = 0 t ( 2 t t 2 ) d t 0 2 ( 2 x x 2 ) d x = 3 x 2 x 3 4 ③0<t<2,P\{x\leq t\}=\frac{∫_0^t(2t-t^2)dt}{∫_0^2(2x-x^2)dx}=\frac{3x^2-x^3}{4}

t = F X ( x ) = { 0 x≤0 3 4 x 2 1 4 x 3 0< x < 2 1 x≥2 ∴t的分布函数=F_X(x)= \begin{cases} 0 &\text{x≤0}\\ \frac{3}{4}x^2-\frac{1}{4}x^3 &\text{0< x < 2}\\ 1&\text{x≥2}\\ \end{cases}

t = f X ( x ) = { 3 2 x 3 4 x 2 0<x<2 0 其他 ∴t的概率密度=f_X(x)= \begin{cases} \frac{3}{2}x-\frac{3}{4}x^2 & \text{0<x<2}\\ 0&\text{其他}\\ \end{cases}

参考:https://zhidao.baidu.com/question/1734677140991479667.html
https://wenku.baidu.com/view/8ca15d14a66e58fafab069dc5022aaea998f4132.html

2020,03,17

1、 X λ > 0 Y = [ x ] 设X服从参数λ>0的指数分布,求Y = [x]的分布

Y 可以看出Y是离散型的,可以直接计算分布律

P { Y = k } = P { [ x ] = k } = P { k x < k + 1 } = k k + 1 λ e λ x d x P\{Y = k\}=P\{[x]=k\}=P\{k≤x<k+1\}=∫_k^{k+1}λe^{-λx}dx

k k + 1 λ e λ x d x = e λ x k k + 1 = e λ ( k + 1 ) + e λ k ∫_k^{k+1}λe^{-λx}dx=-e^{-λx}|_k^{k+1}=-e^{-λ(k+1)}+e^{-λk}

2、 X N ( 0 , 1 ) Y = X X X 1 X > 1 Y 设随机变量X~N(0, 1),Y=X或-X,视|X|≤1或|X|>1而定,求Y的分布

φ ( x ) + φ ( x ) = 1 用到的性质:正态分布φ(x)+φ(-x)=1

Y = { X |x|≤ 1 X |x|>1 Y= \begin{cases} X &\text{|x|≤ 1}\\ -X &\text{|x|>1} \end{cases}

y < 1 P { Y y } = P { X y } = P { X y } = 1 P { X < y } = 1 φ ( y ) = φ ( y ) ①当y<-1时,P\{Y\leq y\}=P\{-X\leq y\}=P\{X\geq -y\}=1-P\{X<-y\}=1-φ(-y)=φ(y)

1 y 1 P { Y y } = P { Y < 1 } + P { 1 Y y } = P { Y < 1 } + P { 1 X y } = φ ( 1 ) + φ ( y ) φ ( 1 ) = φ ( y ) ②当-1\leq y \leq 1时,P\{Y\leq y\}=P\{Y<-1\}+P\{-1\leq Y\leq y\}=P\{Y<-1\}+P\{-1\leq X\leq y\}=φ(-1)+φ(y)-φ(-1)=φ(y)

y > 1 P { Y y } = P { Y < 1 } + P { 1 Y 1 } + P { 1 < Y < y } = P { Y < 1 } + P { 1 Y 1 } + P { y < X < 1 } = φ ( 1 ) + φ ( 1 ) φ ( 1 ) + φ ( 1 ) φ ( y ) = 1 φ ( y ) = φ ( y ) ③当y>1时,P\{Y\leq y\}=P\{Y<-1\}+P\{-1\leq Y\leq 1\}+P\{1<Y<y\}=P\{Y<-1\}+P\{-1\leq Y\leq 1\}+P\{-y<X<-1\}=φ(-1)+φ(1)-φ(-1)+φ(-1)-φ(-y)=1-φ(-y)=φ(y)

Y = φ ( y ) 综上所述,Y=φ(y)

3、 X N ( 0 , 1 ) e X X 设X~N(0,1),分别求e^X和|X|的概率密度函数

1 X N ( 0 , 1 ) f ( x ) = 1 2 p i e x 2 2 x ( , + ) 1)因为X ~ N(0,1),所以f(x)=\frac{1}{\sqrt{2pi}}e^{-\frac{x^2}{2}},x∈(-∞, +∞)

y = e x ( 0 , + ) x = l n y x = 1 y ∴y=e^x∈(0, +∞),x=lny,x'=\frac{1}{y}

f Y ( y ) = f X ( x ) x = 1 y 2 p i e l n y 2 2 y ( 0 , + ) f_Y(y)=f_X(x)*x'=\frac{1}{y\sqrt{2pi}}e^{-\frac{lny^2}{2}},y∈(0,+∞)

f Y ( y ) = { 1 y 2 p i e l n y 2 2  y∈(0,+∞) 0 其他 ∴f_Y(y)= \begin{cases} \frac{1}{y\sqrt{2pi}}e^{-\frac{lny^2}{2}} &\text{ y∈(0,+∞)}\\ 0 &\text{其他} \end{cases}

2 f X ( x ) = 1 2 p i e x 2 2 x ( , + ) y [ 0 , + ) 2)f_X(x)=\frac{1}{\sqrt{2pi}}e^{-\frac{x^2}{2}},x∈(-∞, +∞),y∈[0,+∞)

F Y ( y ) = P { Y y } = P { X y } = P { y X y } = F X ( y ) F X ( y ) F_Y(y)=P \{Y \leq y\}=P\{|X|\leq y\}=P\{-y \leq X \leq y \}=F_X(y)-F_X(-y)

f Y ( y ) = F Y ( y ) = [ F X ( y ) F X ( y ) ] = F X ( y ) F X ( y ) ( 1 ) = F X ( y ) + F X ( y ) = f X ( y ) + f X ( y ) f_Y(y)=F_Y'(y)=[F_X(y)-F_X(-y)]'=F_X'(y)-F_X'(-y)(-1)=F_X'(y)+F_X'(-y)=f_X(y)+f_X(-y)

X Y ⭐题型总结:已知X的概率密度,求Y的概率密度

1 Y 1)当Y单调可导时

X Y ①先根据X的定义域求出Y的定义域

x y ②再求出x关于y的导数

f Y ( y ) = f X ( y ) = f X ( x ) x x x y ③最后f_Y(y)=f_X(y)=f_X(x)*x',将x和x'关于y的表达式代入即可

写出概率密度函数,不要漏掉其他的情况

2 ) Y 2)当Y非单调可导时

X Y ①先根据X的定义域求出Y的定义域

Y X F Y ( y ) = P ( Y y ) = P ( g ( X ) y ) = P ( a X b ) = F X ( b ) F X ( a ) ②再将Y的概率密度转化为X的概率密度,F_Y(y)=P(Y\leq y)=P(g(X)\leq y)=P(a\leq X\leq b)=F_X(b)-F_X(a)

f Y ( y ) = F Y ( y ) = [ F X ( b ) F X ( a ) ] = f X ( b ) b f X ( a ) a ③f_Y(y)=F_Y'(y)=[F_X(b)-F_X(a)]'=f_X(b)b'-f_X(a)a'

写出概率密度函数,不要漏掉其他的情况

2020,03,31

2、设随机变量(X, Y)的联合密度为P(x, y)=(1+xy)/4,|x|, |y|<1,
问:(1)X与Y独立吗(2) X 2 X^2 Y 2 Y^2 独立吗

( 1 ) (1)

F ( a , b ) = P { X a , Y b } F(a,b)=P\{X\leq a, Y \leq b\}

f ( x , y ) = ( 1 + x y ) / 4 f(x,y)=(1+xy)/4

f X ( x ) = 1 1 [ ( 1 + x y ) / 4 ] d y = 1 / 2 f_X(x)=∫_{-1}^{1}[(1+xy)/4]dy=1/2

f Y ( y ) = 1 1 [ ( 1 + x y ) / 4 ] d x = 1 / 2 f_Y(y)=∫_{-1}^{1}[(1+xy)/4]dx=1/2

f ( x , y ) f X ( x ) f Y ( y ) X Y ∵f(x,y)≠f_X(x)*f_Y(y),∴X和Y不独立

( 2 ) (2)

P { X 2 a , Y 2 b } = P { a X a , b Y b } = a a d x b b [ ( x + x y ) / 4 ] d y = a b P\{X^2\leq a,Y^2\leq b\}=P\{-\sqrt{a}\leq X \leq \sqrt a, -\sqrt{b}\leq Y \leq \sqrt b\}=∫_{-\sqrt a}^{\sqrt a}dx∫_{-\sqrt b}^{\sqrt b}[(x+xy)/4]dy=\sqrt{ab}

P { X 2 a } = P { a X a , 1 Y 1 } = 1 1 d x a a [ ( x + x y ) / 4 ] d y = a P\{X^2\leq a\}=P\{-\sqrt{a}\leq X \leq \sqrt a, -1\leq Y \leq 1\}=∫_{-1}^{1}dx∫_{-\sqrt a}^{\sqrt a}[(x+xy)/4]dy=\sqrt{a}

P { Y 2 b } = P { 1 X 1 , b Y b } = 1 1 d y b b [ ( x + x y ) / 4 ] d y = b P\{Y^2\leq b\}=P\{-1\leq X \leq 1,-\sqrt{b}\leq Y \leq \sqrt b\}=∫_{-1}^{1}dy∫_{-\sqrt b}^{\sqrt b}[(x+xy)/4]dy=\sqrt{b}

5、设X、Y相互独立,X服从参数为1/2的01分布,而Y服从(0,1)上的均匀分布,求X+Y的分布

P ( X + Y z ) = { 0 x≤0 z 2 0< x < 2 1 x≥2 P(X+Y\leq z)= \begin{cases} 0 &\text{x≤0}\\ \frac{z}{2} &\text{0< x < 2}\\ 1&\text{x≥2}\\ \end{cases}

0 z < 1 ①0\leq z< 1

P { X + Y z } = P { X = 0 , Y z } = P { X = 0 } P { Y z } = 1 / 2 z = z / 2 P\{X+Y\leq z\}=P\{X=0,Y\leq z\}=P\{X=0\}*P\{Y\leq z\}=1/2*z=z/2

1 z < 2 ②1\leq z< 2

P { X + Y z } = P { X = 0 , Y z } + P { X = 1 , Y z 1 } = P { X = 1 } P { Y z 1 } = 1 / 2 + ( z 1 ) / 2 = z / 2 P\{X+Y\leq z\}=P\{X=0,Y\leq z\}+P\{X=1,Y\leq z-1\}=P\{X=1\}*P\{Y\leq z-1\}=1/2+(z-1)/2=z/2

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