Data Management 0416 EX01-3

EX01

dta <- read.table("hs0.txt", header=T)

dta.asian <- subset(dta, race=="asian") #只挑亞洲學生
r0 <- cor(dta.asian$math, dta.asian$socst) #亞洲學生math和scost的相關r0

nIter <- 1001 #設定參數
i=1
cnt=0
repeat{
  new <- sample(dta.asian$read)  #隨機排序read
  r1 <- cor(new, dta.asian$math) #新排序後的read和math的相關r1
  i=i+1
  if ( r0 <= r1 ) cnt <- cnt+1 #累計r0 <= r1的次數
  if (i >= nIter) break
}
cnt/nIter

## [1] 0.03496503

EX02

#透過function顯示以nlter設置次數的隨機的x,y之plot(原設定為512，以下設定3示意)
Brownian <- function(n = 5, pause = 0.05, nIter = 3, ...) {
    x = rnorm(n)
    y = rnorm(n)
    i = 1
    repeat {
      plot(x, y, ...)
      text(x, y, cex = 0.5)
      x = x + rnorm(n)
      y = y + rnorm(n)
      Sys.sleep(pause)
      i = i + 1
      if(i > nIter) break
    }
} 
Brownian(xlim = c(-20, 20), ylim = c(-20, 20), 
    pch = 21, cex = 2, col = "cyan", bg = "lavender") 

EX03

library("magrittr")
newsim<- function(n){
  m <- matrix(nrow=n, ncol=2) 
  m[, 1] <- runif(n)
  m[, 2] <- rnorm(n)
Gender <- ifelse(m[, 1]<0.505, "Male", "Female")
Height <- ifelse(m[, 1]<0.505, 170 + 7*m[, 2],160 + 5*m[, 2]) %>% round(2)
Person <- data.frame(Gender,Height)
return(Person)
}

newsim(10)

##    Gender Height
## 1    Male 171.05
## 2    Male 172.98
## 3    Male 164.73
## 4    Male 161.88
## 5    Male 164.94
## 6  Female 157.21
## 7    Male 169.37
## 8  Female 167.34
## 9  Female 157.39
## 10   Male 161.43