Untitled

Statistic <- c(68,85,74,88,63,78,90,80,58,63)
Math <- c(85,91,74,100,82,84,78,100,51,70)


plot(Statistic,Math,
     pch = 17,
     col= "skyblue",
     main ="班上的體重與身高",
     xlab ="體重",
     ylab ="身高")

hist(Statistic,
     col= "lightyellow",
     main ="班上的體重與身高",
     xlab ="體重",
     ylab ="次數")

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

# Create data
data <- data.frame(
  clubs=c("Entertainment and leisure","Knowledge reading","Sports competition","Scientific innovation","Charity activities") ,  
  frequency=c(185,82,36,28,25)
  )

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

data<- c(44,55,82,67,106)
labels <- c("Entertainment and leisure","Knowledge reading","Sports competition","Scientific innovation","Charity activities")
pie(data,labels,main ="proportion of clubs that college students most like to join", col=heat.colors(length(data)))

Data <- read.csv("D:/1.csv")
stem(Data$Japanese)

## 
##   The decimal point is 1 digit(s) to the right of the |
## 
##   4 | 9
##   5 | 139
##   6 | 13
##   7 | 9
##   8 | 49
##   9 | 1

Japanese<-c(84,63,61,49,89,51,59,53,79,91)

mean(Japanese)

## [1] 67.9

median(Japanese)

## [1] 62

min(Japanese)

## [1] 49

max(Japanese)

## [1] 91

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

## [1] 49

sd(Japanese)

## [1] 16.25115

var(Japanese)

## [1] 264.1

Q1 <- quantile(Japanese, 1 / 4)
print(Q1)

##  25% 
## 54.5

Q3 <- quantile(Japanese, 3 / 4) 
print(Q3)

##   75% 
## 82.75