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

plot(S,M,
     pch = 23,
     col= "skyblue",
     main ="統計成績與數學成績之散佈圖",
     xlab ="統計",
     ylab ="數學")

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

# Load ggplot2
library(ggplot2)

# Create data
data <- data.frame(
  name=c("娛樂休閒","知識閱讀","體育競技","科學創新","公益活動") ,  
  value=c(185,82,36,28,25)
  )

# Bar plot
ggplot(data, aes(x=name, y=value)) + 
  geom_bar(stat = "identity")

data2<- c(185,82,36,28,25)
labels <- c("娛樂休閒","知識閱讀","體育競技","科學創新","公益活動")

pie(data2,labels,main ="社團類型", col=heat.colors(length(data)))

# Library
library(ggplot2)
 
# plot
ggplot(data, aes(x=name, y=value)) +
  geom_segment( aes(x=name, xend=name, y=0, yend=value)) +
  geom_point( size=5, color="red", fill=alpha("orange", 0.3), alpha=0.7, shape=21, stroke=2) 

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

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

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

mean(v) 

## [1] 67.9

median(v)

## [1] 62

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

## [1] 49

sd(v)

## [1] 16.25115

var(v)

## [1] 264.1

Q1 <- quantile(J, 1 / 4) 
Q2 <- quantile(J, 2 / 4) 
Q3 <- quantile(J, 3 / 4) 

P1 <- quantile(J, 1 / 10) 
P2 <- quantile(J, 2 / 10) 
P3 <- quantile(J, 3 / 10) 

P5 <- quantile(J, 5 / 10) 

Q1

##  25% 
## 54.5

Q3

##   75% 
## 82.75