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@LetticiaNicoli
Last active May 29, 2019 22:45
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R - Amostras e Simulações
#Amostras e Simulações
#Distribuição uniforme
runif(n=2, min = 1, max = 10)
#Avalia probabilidade
dunif(x= 8, min = 1, max = 10)
#número máximo nao é sorteado
#Avalia probabilidade acumulaa
punif(q= 2, min = 1, max = 10)
#Amostra a partir de um domínio
set.seed(1) #coloca marcador para que o sorteio sempre seja igual
amostra = c( "T", "R", "I", "A", "N", "G", "U", "L", "O", "S")
sample(x = amostra, replace = FALSE)
sample(x = amostra, replace = TRUE)
sample(x = amostra, size = 5)
sample(x = amostra, size = 10, replace = TRUE,
prob = c(1, 1, 5, 1, 1, 1, 1, 1, 1, 5))
#Exercicio
?data.frame
#Dimensao
dim(airquality)
#Resumo
summary(airquality)
#Amostra 10 primeiros registros
airquality[1:10,] #ou head(airquality, n=10)
#Amostra 10 linhas aleatorias
set.seed(20)
airquality[sample(nrow(airquality), 10),]
#Simulano um modelo linear
set.seed(20)
b0 = rep(0.5, times = 100)
b1 = rep(2, times = 100)
x = rnorm(n = 100, mean = 0, sd = 1)
e = rnorm(n = 100, mean = 0, sd = 2)
valor = b0 + (b1 * x) + e
library(plotly)
plot_ly( x = x, y = valor, type = "scatter" )
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