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)



plot(we,we2,
     pch = 17,
     col= "skyblue",
     main ="班上的統計與數學分數",
     xlab ="統計",
     ylab ="數學")

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

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

# Load ggplot2
library(ggplot2)
# 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)
  )

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

data<- 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(data,labels,main ="次數圓餅圖", col=heat.colors(length(data)))

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

## [1] 74.7

median(we) 

## [1] 76

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

## [1] 63

sd(we)

## [1] 11.32402

var(we)

## [1] 128.2333

Q1 <- quantile(we, 1 / 4)
Q3 <- quantile(we, 3 / 4)
Q1

##   25% 
## 64.25

Q3

##   75% 
## 83.75