Ejercicios R, R - rextester

Ejercicios R

a<-c(3,4,5)

#distribucion binomial
dbinom(5,10,0.8)

print(a)

dpois(8,7.1)

pnorm(12,10,8)
      
vector<-c(rpois(1000,8.2))
vector
hist(vector)

vector<-c(rgeom(100000,.4))
vector
hist(vector, col='green',main='Datos',xlab = 'Acumulado', ylab = 'Valores',xlim = c(0,5))

x<-seq(165,175, by=0.5)
dnorm(x,170,12)
curve(dnorm(x,170,12),xlim = c(130,210), col='red', lwd=5,xlab = 'x',ylab = 'f(x)',main='Distribucion')

a<-pnorm(150+1*12,150,12)-pnorm(150-1*12,150,12)
b<-pnorm(150+2*12,150,12)-pnorm(150-2*12,150,12)
c<-pnorm(150+3*12,150,12)-pnorm(150-3*12,150,12)
d<-pnorm(150+4*12,150,12)-pnorm(150-4*12,150,12)

a
b
c
d

a<-pnorm(12,10,8)

#Ejercicio 1  P( m-G <= x <= m+G ) = 99%

pnorm(150+3*12,150,12)-pnorm(150-3*12,150,12)

#Ejercicio 2 Crear un vector de una binomial 10000 p=1/2

vector<-c(rgeom(10000,.5))
vector

#Ejercicio 3 Graficar una exponencial con parametro lambda=15

x<-seq(165,175, by=0.5)
curve(dexp(x,15),xlim = c(0,0.5), col='red', lwd=5,xlab = 'x',ylab = 'f(x)',main='Distribucion exponencial')

#Graficar una normal N(5000,2500)

x<-seq(165,175, by=0.5)
curve(dnorm(x,5000,50),xlim = c(4800,5200), col='green', lwd=5,xlab = 'x',ylab = 'f(x)',main='Distribucion normal')


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