期中作業

#1
math <- c(85,91,74,100,82,84,78,100,51,70)
Statistic <- c(68,85,74,88,63,78,90,80,58,63)

plot(math,Statistic,
     pch = 15,
     col= "skyblue",
     main="數學成績和統計成績",
     xlab="數學",
     ylab="統計")

#2
hist(math,
     col="skyblue",
     main="數學成績",
     xlab="數學",
     ylab="人數")

#3
library(ggplot2)

data <- data.frame(
  社團類型=c("娛樂休閒","知識閱讀","體育競技","科學創新","公益活動") ,  
  次數=c(185,82,36,28,25)
  )

ggplot(data, aes(x=社團類型, y=次數)) + 
  geom_bar(stat = "identity", width=0.2) 

#4
次數=c(185,82,36,28,25)
社團類型=c("娛樂休閒","知識閱讀","體育競技","科學創新","公益活動") 
 

pie(次數,社團類型)

#5
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ lubridate 1.9.4     ✔ tibble    3.2.1
## ✔ purrr     1.0.4     ✔ tidyr     1.3.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

data <- data.frame(
  社團類型=c("娛樂休閒","知識閱讀","體育競技","科學創新","公益活動"),
  次數=c(185,82,36,28,25)
)
 

ggplot(data, aes(x=社團類型, y=次數)) +
  geom_segment( aes(x=社團類型, xend=社團類型, y=0, yend=次數)) +
  geom_point( size=5, color="red", fill=alpha("orange", 0.3), alpha=0.7, shape=21, stroke=2) 

#6
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

#7
Japanese=c(84,63,61,49,89,51,59,53,79,91)

mean(Japanese)      #平均數

## [1] 67.9

median(Japanese)    #中位數

## [1] 62

as.numeric(names(table(Japanese)))[which.max(table(Japanese))] #眾數

## [1] 49

sd(Japanese)  #標準差

## [1] 16.25115

var(Japanese) #變異數

## [1] 264.1

quantile(Japanese,1/4)#第一四分位數?

##  25% 
## 54.5

quantile(Japanese,3/4)#第三四分位數?

##   75% 
## 82.75