Normal Padrão:
## Carregando pacotes exigidos: car
## Carregando pacotes exigidos: carData
## Carregando pacotes exigidos: sandwich
.x <- seq(-3.291, 3.291, length.out=1000)
1. P (x < 0) = 0.5
2. P ( 0 < x < 0.11) = 0.04380
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="n", ylab="Densidade",
regions=list(c(0, 0.11)), col=c('royal blue', '#BEBEBE'), legend=FALSE)
3. P (-2.2 < x < 0.12) = P (-2,2 < x < 0) + P (0 < x < 0,12) = 0.4783 + 0.04776 = 0.52606
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(-2.2, 0.12)), col=c('pink', '#BEBEBE'), legend=FALSE)
4. P (-1 < x < 2.1) = P (-1 < x < 0) + P (0 < x < 2.1) = 0.34134 + 0.48214 = 0.82348
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(-1, 2.1)), col=c('dark red', '#BEBEBE'), legend=FALSE)
5. P (0 < x < 1.83) = 0.46638
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(0, 1.83)), col=c('dark green', '#BEBEBE'), legend=FALSE)
6. P (-0.87 < x 1.54) = P (-0.87 < x < 0) + P (0 < x < 1.54) = 0.30785 + 0.43822 = 0.74607
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(-0.87, 1.54)), col=c('dark blue', '#BEBEBE'), legend=FALSE)
7. P (x=1.54) = 0
Se marcamos esse ponto no gráfico, teríamos uma linha/reta e o plotdistr não delimita uma área, portanto, consideramos nula.
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(1.54)), col=c('light yellow','#BEBEBE'), legend=FALSE)
8. P (x > 2.5) = 0.5 - 0.49379 = 0.00621
2.5 até 0 = 0.49379
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(2.5, 10)), col=c('black', '#BEBEBE'), legend=FALSE)
9. P (x > -2) = 0.47725 + 0.5 = 0.97725
-2 até 0 = 0.47725
plotDistr(.x, dnorm(.x, mean=0, sd=1), cdf=FALSE, xlab="x", ylab="Densidade",
regions=list(c(-2, 10)), col=c('purple', '#BEBEBE'), legend=FALSE)
