Distribuicao Normal

Exercícios de Distribuição Normal

library(RcmdrMisc)

## Carregando pacotes exigidos: car

## Carregando pacotes exigidos: carData

## Carregando pacotes exigidos: sandwich

1- P(X<0)= 0,6

.x <- seq(-3.291, 3.291, length.out=1000)    
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z", 
          ylab="Densidade",regions=list(c(0,4)), 
          col=c('GREEN'), legend=FALSE)

2- P(0<X<0,11)

P(0<X<0,11) = 0,04380

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", 
          ylab="Densidade",regions=list(c(0, 0.11)), 
          col=c('pink'), legend=FALSE)

3 - P(-2,2<X<0,12)= 0,53386

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", 
          ylab="Densidade",regions=list(c(-2.2, 0.12)), 
          col=c('purple'), legend=FALSE)

4- P(-1<X<2,1) = 0,82348

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z", 
          ylab="Densidade",regions=list(c(-1,0),c(0,2.1)), 
          col=c('pink','skyblue'), legend=FALSE)

5- P(0<X<1,83)

P(0<X<1,83) = 0,46638

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z", 
          ylab="Densidade",regions=list(c(0,1.83)), 
          col=c('gold'), legend=FALSE)

6- P(-0,87<X<1,54) = 0,74607

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z", 
          ylab="Densidade",regions=list(c(-0.87,0),c(0,1.54)), 
          col=c('pink','Gray'), legend=FALSE)

7 - P(X=1,54)

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", 
          ylab="Densidade",regions=list(c(1.54,10)), 
          col=c('yellow'), legend=FALSE)

8 - P(x>2,5)=0,00621

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", 
          ylab="Densidade",regions=list(c(2.5,10)), 
          col=c('skyblue'), legend=FALSE)

9 - P(x>-2)=0,97725

plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z", 
          ylab="Densidade",regions=list(c(-2,4)), 
          col=c('pink'), legend=FALSE)