Homework 3

library(tidyverse)

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library(readxl)

district<-read_excel("district.xls")

new_df<-district %>% select(DISTNAME,DPETSPEP,DPFPASPEP)

summary(new_df$DPFPASPEP)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##   0.000   5.800   8.900   9.711  12.500  49.000       5

summary(new_df$DPETSPEP)

##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    0.00    9.90   12.10   12.27   14.20   51.70

DPFPASPEP is the variable that has 5 missing values.

new_df2<-new_df%>% filter(!is.na(DPFPASPEP))

Therea 1202 observations left.

ggplot(new_df2,aes(x=DPFPASPEP,y=DPETSPEP))+geom_point()

The interpretation is that both variables are correlated.