Kiki

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="blue",
     xlab="統計成績",
     ylab="數學成績",
     main="班級的統計和數學成績")

hist(Math,
     col= "lightyellow",
     main ="班上的統計成績與數學成績",
     xlab ="數學成績",
     ylab ="人數")

library(ggplot2)

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

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

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

pie(data,labels,main ="社團的比例", col=heat.colors(length(data)))

library(readxl)

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

Data <- read.csv("C:/1.csv")


stem(Japanese,scale = 2)

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

mean(Japanese)

## [1] 67.9

median(Japanese)

## [1] 62

mode(Japanese)

## [1] "numeric"

sd(Japanese)

## [1] 16.25115

var(Japanese)

## [1] 264.1

Q1 <- quantile(Japanese, 1/4)

Q1

##  25% 
## 54.5

Q3 <- quantile(Japanese, 3/4)

Q3

##   75% 
## 82.75