3.1随机抽样

sample(1:40,5)#从1到40中随机取5个数，默认为无放回抽样

[1] 19 3 20 35 13

sample(c("H","t"),10,replace=T)#模拟10次投掷硬币，replace=T有放回抽样参数

[1] “H” “H” “t” “t” “t” “H” “t” “H” “t” “t”

3.2概率论计算和排列组合

sample(c("succ","fail"),10,replace=T,prob = c(0.9,0.1))#prob参数模拟具有不相等概率的数据

[1] “succ” “succ” “succ” “succ” “succ” “succ” “succ” “succ” “succ” “succ”

1/prod(40:36)#累乘函数

[1] 1.266449e-08

prod(5:1)/prod(40:36)

[1] 1.519738e-06

1/choose(40,5)#choose为组合函数

[1] 1.519738e-06

3.3离散分布

3.4连续分布

3.5R中的内置分布

3.5.1密度

x<-seq(-4,4,0.1)
plot(x,dnorm(x),type = "l")#绘制正态分布的密度函数线

curve(dnorm(x),from = -4,to=4)#同上

x<-0:50
plot(x,dbinom(x,size = 50,prob=.33),type = "h")#绘制n=50，p=0.33的二项分布图形，h为针形图

3.5.2累积分布函数

1-pnorm(160,mean=132,sd=13)#pnorm函数返回一个在给定均值为132，标准差为13的正态分布下取到小于160的概率

[1] 0.01562612

pbinom(16,size=20,prob = .5)#

[1] 0.9987116

1-pbinom(15,size=20,prob = .5)

[1] 0.005908966

pbinom(4,20,.5)#参数以正确的顺序给出，可不使用size和prob关键字

[1] 0.005908966

1-pbinom(15,20,.5)+pbinom(4,20,.5)#1-pbinom为16或更多

[1] 0.01181793

3.5.3分位数

xbar<-83
sigma<-12
n<-5
sem<-sigma/sqrt(n)#标准差为
sem

[1] 5.366563

xbar+sem*qnorm(0.025)#2.5%分位数点

[1] 72.48173

xbar+sem*qnorm(0.975)#97.5%分位数点

[1] 93.51827

3.5.4随机数

rnorm(10)

[1] 0.41956052 0.25759940 0.69012141 -0.47932737 -1.02003932
[6] 0.31874663 -0.53690831 -0.13565610 0.09019251 0.37229407

rnorm(10)

[1] 1.5106657 -1.0306662 -1.0183139 -0.4975699 0.5327055 -1.8277768
[7] 1.7719537 0.6349547 1.3073196 0.3095579

rnorm(10,mean=7,sd=5)#控制均值与方差

[1] 11.9441279 -3.6666113 0.4073246 2.0410807 10.4215748 5.7507122
[7] 7.4608988 12.4506186 4.4587588 -1.9938817

rbinom(10,size=20,prob=.5)#控制二项分布的n与p

[1] 6 11 11 6 8 10 14 11 14 10