i

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 = 01,
     col= "#FFE632",
     main ="統計成績與數學成績",
     xlab ="統計成績",
     ylab ="數學成績")

ii

hist(Statistic,
     col= "skyblue",
     main ="統計成績",
     xlab ="分數",
     ylab ="人數")

iii

data <- data.frame(
  類型=c("1公益活動","2科學創新","3體育競技","4知識閱讀","5娛樂休閒"),
  次數=c(185,82,36,28,25))
barplot(height=data$次數, names=data$類型,
     col= "#FFE632",
     main ="大學生最喜歡參加的社團的次數分配表",
     xlab ="類型",
     ylab ="次數",)

#iv

data<- c(185,82,36,28,25)
labels <- c("1公益活動","2科學創新","3體育競技","4知識閱讀","5娛樂休閒")

pie(data,labels,main ="大學生最喜歡參加的社團的次數分配表", col=heat.colors(length(data)))

#v

library(readr)
Data <- read.csv("C:/Users/USER/Downloads/table1_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

#vi

library(readr)
Data <- read.csv("C:/Users/USER/Downloads/table1_1.csv")
mean(Data$Japanese)
## [1] 67.9
median(Data$Japanese)
## [1] 62
as.numeric(names(table(Data$Japanese)))[which.max(table(Data$Japanese))] 
## [1] 49
sd(Data$Japanese)
## [1] 16.25115
var(Data$Japanese)
## [1] 264.1
Q1 <- quantile(Data$Japanese, 1 / 4) 
Q3 <- quantile(Data$Japanese, 3 / 4) 

Q1
##  25% 
## 54.5
Q3
##   75% 
## 82.75