install.packages("https://cran.rstudio.com/bin/windows/contrib/4.1/faraway_1.0.7.zip", repos = F)
## 將程式套件安載入 'C:/Users/user/Documents/R/win-library/4.1'
## (因為 'lib' 沒有被指定)
## Warning: unable to access index for repository FALSE/src/contrib:
##   網址 'FALSE/src/contrib/PACKAGES' 不支援方案格式
## Warning: package 'https://cran.rstudio.com/bin/windows/contrib/4.1/faraway_1.0.7.zip' is not available for this version of R
## 
## A version of this package for your version of R might be available elsewhere,
## see the ideas at
## https://cran.r-project.org/doc/manuals/r-patched/R-admin.html#Installing-packages
## Warning: unable to access index for repository FALSE/bin/windows/contrib/4.1:
##   網址 'FALSE/bin/windows/contrib/4.1/PACKAGES' 不支援方案格式
library(faraway)
## Warning: 套件 'faraway' 是用 R 版本 4.1.3 來建造的
library(lattice)
## 
## 載入套件：'lattice'
## 下列物件被遮斷自 'package:faraway':
## 
##     melanoma

決定使用fortune這一筆資料

data("fortune")

檢視六筆資料

head(fortune)
##   wealth age region
## 1   37.0  50      M
## 2   24.0  88      U
## 3   14.0  64      A
## 4   13.0  63      U
## 5   13.0  66      U
## 6   11.7  72      E

檢視資料結構

str(fortune)
## 'data.frame':    232 obs. of  3 variables:
##  $ wealth: num  37 24 14 13 13 11.7 10 8.2 8.1 7.2 ...
##  $ age   : int  50 88 64 63 66 72 71 77 68 66 ...
##  $ region: Factor w/ 5 levels "A","E","M","O",..: 3 5 1 5 5 2 3 5 5 2 ...

看看每個區域富豪的情況

table(fortune$region)
## 
##  A  E  M  O  U 
## 38 80 22 29 63

檢視財富的狀況

summary(fortune$wealth)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##   1.000   1.300   1.800   2.684   3.000  37.000

各區域中財富的平均數

aggregate(wealth ~ region, data = fortune, FUN = mean)
##   region   wealth
## 1      A 2.621053
## 2      E 2.207500
## 3      M 4.263636
## 4      O 2.234483
## 5      U 2.984127

各區域中財富的標準差

aggregate(wealth ~ region, data = fortune, FUN = sd)
##   region   wealth
## 1      A 2.170833
## 2      E 1.597686
## 3      M 7.657150
## 4      O 1.264989
## 5      U 3.632524

畫圖看地區與財富間關係

densityplot(~ wealth, groups = region, data = fortune, xlab = 'Wealth', lty = c(1,2,3,4,5),
            plot.points = F, type = "g")

畫boxplot圖看地區與財富間關係

boxplot(wealth ~ region, fortune, col = "blue", border = "black")

畫圖看不同區域財富的資料分數直方圖

histogram(~ wealth | region, data = fortune, xlab = 'Wealth', ylab='機率',
          type = 'density', layout = c(5, 1))

boxplot(wealth ~ region, fortune, xlab = "Region", ylab = "Wealth", frame = F, col = c("#00AFBB", "#E7B800", "#FC4E07", "#0000FF"))

不同區域間財富的平均數標準誤

aggregate(wealth ~ region, data = fortune, function(x) sd(x)/sqrt(length(x)))
##   region    wealth
## 1      A 0.3521557
## 2      E 0.1786268
## 3      M 1.6325099
## 4      O 0.2349026
## 5      U 0.4576550

不同區域間年齡的平均標準誤

aggregate(age ~ region, data = fortune, function(x) sd(x)/sqrt(length(x)))
##   region      age
## 1      A 1.637225
## 2      E 1.685748
## 3      M 4.163297
## 4      O 2.471913
## 5      U 1.508630

年齡與財富散佈圖

plot(fortune$wealth, fortune$age, col=blues9, pch = 16, xlab = "Wealth", ylab = "Age")

#看不同區域間，財富與年齡間的關係是否類似

xyplot(age ~ wealth |  region, data = fortune, xlab = 'Wealth', ylab = 'Age',
       type = c("g", "p", "r"), cex = 0.1, layout = c(5, 1))

資料結果說明不同區域間皆有貧富差距(看Boxplot圖便可知，形狀很扁)