Q1: Summarize the backpain{HSAUR3} into the following format

#先把資料叫出來
library(HSAUR3)
## Loading required package: tools
dta1 <- backpain
head(dta1) #看一下資料
##   ID  status driver suburban
## 1  1    case    yes      yes
## 2  1 control    yes       no
## 3  2    case    yes      yes
## 4  2 control    yes      yes
## 5  3    case    yes       no
## 6  3 control    yes      yes
library(magrittr)
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
#使用group_by,先將資料分層後再做計算
dta1 %>% group_by (driver, suburban) %>% 
            summarise(case=sum(status =='case'),
                      control=sum(status=='control'),
                      total=n())
## # A tibble: 4 x 5
## # Groups:   driver [2]
##   driver suburban  case control total
##   <fct>  <fct>    <int>   <int> <int>
## 1 no     no          26      47    73
## 2 no     yes          6       7    13
## 3 yes    no          64      63   127
## 4 yes    yes        121     100   221

Q2: Merge the two data sets: state.x77{datasets} and USArrests{datasets} and compute all pair-wise correlations for numerical variables.

Is there anything interesting to report?
#先把資料叫出來
library(datasets)
#看一下第一筆資料的型態
class(state.x77)
## [1] "matrix"
#資料型態更改成 data.frame，並指定資料名稱
dta2_1 <- as.data.frame(state.x77) 
#確認第二筆資料的型態
class(USArrests)
## [1] "data.frame"
#指定資料名稱
dta2_2 <-USArrests
#合併兩筆資料，並移除遺漏值
dta2 <- merge(dta2_1, dta2_2, rm.na =T)
#計算相關係數，並畫圖找出關聯性
library(corrplot)
## corrplot 0.84 loaded
round(cor(dta2),2) %>% corrplot(., method= "number")

##Murder與 Illiteracy, Assault, Rape有強烈的正相關； ##Illiteracy與Life Exp, HS Grd, Fros有強烈的負相關。

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