Untitled

we <- c(68,85,74,88,63,78,90,80,58,63)

we2 <- c(85,91,74,100,82,84,78,100,51,70)
mean(we)      

## [1] 74.7

plot(we,we2,
     pch = 17,
     col= "pink",
     main ="成績",
     xlab ="Statistic",
     ylab ="Math")

hist(we,
     col= "lightblue",
     main ="成績",
     xlab ="Statistic",
     ylab ="人數")

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

# Create data
data <- data.frame(
  club=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)
  )

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

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 ="社團的比例", col=heat.colors(length(data2)))

# Libraries
library(ggplot2)

# Plot
ggplot(data, aes(x=club, y=value)) +
  geom_point() + 
  geom_segment( aes(x=club, xend=club, y=0, yend=value))

Data <- read.csv("D:/940918.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

mean(Data$Japanese) 

## [1] 67.9

median(Data$Japanese)

## [1] 62

sd(Data$Japanese)

## [1] 16.25115

var(Data$Japanese) 

## [1] 264.1

Q1 <- quantile(Data$Japanese, 1 / 4) 
Q3 <- quantile(Data$Japanese, 3 / 4)