Documento com os cÔlculos das probabilidades do slide 7 da apresentação sobre a normal (distribuição normal e tabela da norma padrão)

library(RcmdrMisc) 
## Carregando pacotes exigidos: car
## Carregando pacotes exigidos: carData
## Carregando pacotes exigidos: sandwich

1 - P(x > 0) = 0,5

.x <- seq(-3.291, 3.291, length.out=1000)    
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",regions=list(c(0, 4)), col=c('#0080C0', '#BEBEBE'), legend=FALSE)

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

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

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

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

4 - P(-1<X<2,1)

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

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

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

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

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

8 - P(x>2,5)

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)

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)