Exercícios de Distribuição Normal
2- P(0<X<0,11)
P(0<X<0,11) = 0,04380
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z",
ylab="Densidade",regions=list(c(0,0.11)),
col=c('blue'), legend=FALSE)

3- P(-2,2<X<0,12)
P(-2,2<X<0,12) = P(-2,2<X<0) + P(0<X<0,12)
P(-2,2<X<0,12) = P(2,2<X<0) + P(0<X<0,12)
P(-2,2<X<0,12) = 0,48610 + 0,04776
P(-2,2<X<0,12) = 0,53386
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z",
ylab="Densidade",regions=list(c(-2.2,0),c(0,0.12)),
col=c('PINK', 'PURPLE'), legend=FALSE)

4- P(-1<X<2,1)
P(-1<X<2,1) = P(-1<X<0) + P(0<X<2,1)
P(-1<X<2,1) = P(1<X<0) + P(0<x<2,1)
P(-1<X<2,1) = 0,34134 + 0,48214
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('green','red'), 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('blue'), legend=FALSE)

6- P(-0,87<X<1,54)
P(-0,87<X<1,54) = P(-0,87<x<0) + P(0<x<1,54)
P(-0,87<X<1,54) = P(0,87<x<0) + P(0<x<1,54)
P(-0,87<X<1,54) = 0,30785 + 0,43822
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('ORANGE','GREEN'), legend=FALSE)

7- P(X=1,54) (favor explicar o motivo)
8- P(x>2,5)
Se x>0 = 0,5; então
P(x>2,5) = 0,5 - P(0<x<2,5)
P(x>2,5) = 0,5 - 0,49379
P(x>2,5) = 0,00621
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="z",
ylab="Densidade",regions=list(c(2.5,4)),
col=c('SKYBLUE'), legend=FALSE)

9- P(x>-2)
Se x>0 = 0,5; então
P(x>-2) = P (-2<X<0) + 0,5
P(x>-2) = 0,47725 + 0,5
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('DARKBLUE'), legend=FALSE)
