Proyecto 2

df <- read.csv("empleados.csv")
df <- data.frame(df)
df <- mutate(df,a = ifelse(Capacitacion == df[2,2],1,0))

b <- c()
c <- c()
d <- c()
for (i in (1:1000)) {
  a <- sample(1:1000,30,replace=F)
  df1 <- df[a,]
  b <- c(b,mean(df1$Salario))
  c <- c(c,sd(df1$Salario))
  d <- c(d,mean(df1$a)) 
}

df1 <- data.frame(b,c,d)
df <- data.frame(rnorm(10000,79000,3500))
df1 <- data.frame(df1,df)
colnames(df1) <- c("media_sal","sd_sal","media_cap","norm")

df1 <- c(df1[,1],rep(NA,35000))
df1 <- data.frame(df1)
df <- data.frame(rnorm(45000,79000,3500))
df <- data.frame(df,df1)

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.