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weight <- c(55,60,70,75,75)

height <- c(155,160,170,175,175)

mean (weight)

## [1] 67

mean (height)

## [1] 167

median(weight)

## [1] 70

median(height)

## [1] 170

min(weight)

## [1] 55

min(height)

## [1] 155

max(weight)

## [1] 75

max(height)

## [1] 175

as.numeric(names(table(weight)))[which.max(table(weight))] 

## [1] 75

as.numeric(names(table(height)))[which.max(table(height))] 

## [1] 175

sd(weight)  #標準差

## [1] 9.082951

sd(height)  #標準差

## [1] 9.082951

var(weight) #變異數\

## [1] 82.5

var(height) #變異數

## [1] 82.5

plot(weight, height,
     pch = 17,
     col= "darkblue",
     main ="班上的體重與身高",
     xlab ="體重",
     ylab ="身高")

hist(weight,
     col= "black",
     main ="班上的體重與身高",
     xlab ="體重",
     ylab ="生高")

# Load ggplot2
library(ggplot2)
# Load ggplot2
library(ggplot2)

# Create data
data <- data.frame(
 name=c("王曉明","B","C","D","E","F") ,  
  value=c(50,55,63,55,67,43)
  )

# Barplot
ggplot(data, aes(x=name, y=value)) + 
  geom_bar(stat = "identity", width=0.2,  fill="skyblue") 

data<- c(50,23,35,48)
labels <- c("英文系","法文系","德文","翻譯")

pie(data,labels,main ="學生的比例", col=rainbow(length(data)))