Research Paper Data Selection

library(readxl)
district <- read_excel("district.xls")
library(tidyverse)

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obj3 <- district %>% select(DISTNAME,DPETBILP,DPFPABILP)

#1)summary(data$x)
summary(district$DPETBILP)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    0.00    2.90    7.30   12.58   16.80  100.00

summary(district$DPFPABILP)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.1000  0.4000  0.7496  1.0000 26.0000       5

summary(obj3)

##    DISTNAME            DPETBILP        DPFPABILP      
##  Length:1207        Min.   :  0.00   Min.   : 0.0000  
##  Class :character   1st Qu.:  2.90   1st Qu.: 0.1000  
##  Mode  :character   Median :  7.30   Median : 0.4000  
##                     Mean   : 12.58   Mean   : 0.7496  
##                     3rd Qu.: 16.80   3rd Qu.: 1.0000  
##                     Max.   :100.00   Max.   :26.0000  
##                                      NA's   :5

#remove the missing observations
obj3_cleaned <- obj3 %>% filter(!is.na(DPFPABILP))

#2)hist(data$x)
hist(district$DPETBILP)

hist(district$DPFPABILP)

#3)plot(data$x,data$y)
plot(district$DPETBILP,district$DPFPABILP)

#4)cor(data$x,data$y)
cor(obj3_cleaned$DPETBILP,obj3_cleaned$DPFPABILP)

## [1] 0.6103153

There is no correlation between the two variables.