library(readxl)
library(tidyverse)
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## ✔ ggplot2   4.0.1     ✔ tibble    3.3.1
## ✔ lubridate 1.9.4     ✔ tidyr     1.3.2
## ✔ purrr     1.2.1     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
setwd("C:/Users/qfd738-4251/Desktop/My Class Stuff/Monday Class")

district<-read_excel("district.xls")

Question 2

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

Question 3

your_variable_here<-district %>% select(DPETSPEP,DPFPASPEP)
summary(your_variable_here)
##     DPETSPEP       DPFPASPEP     
##  Min.   : 0.00   Min.   : 0.000  
##  1st Qu.: 9.90   1st Qu.: 5.800  
##  Median :12.10   Median : 8.900  
##  Mean   :12.27   Mean   : 9.711  
##  3rd Qu.:14.20   3rd Qu.:12.500  
##  Max.   :51.70   Max.   :49.000  
##                  NA's   :5

Question 4

5 Values are Missing

Question 5

your_variable_here %>% drop_na()
## # A tibble: 1,202 × 2
##    DPETSPEP DPFPASPEP
##       <dbl>     <dbl>
##  1     14.6      28.9
##  2     12.1       8.8
##  3     13.1       8.4
##  4     10.5      10.1
##  5     13.5       6.1
##  6     14.5       9.4
##  7     14.7       9.9
##  8     10.4      10.9
##  9     11.6       9.2
## 10     11.9      10.3
## # ℹ 1,192 more rows

1,202 are left over

Question 7

my_variables_without_NA<-your_variable_here %>% drop_na()
cor(my_variables_without_NA$DPFPASPEP,my_variables_without_NA$DPETSPEP)
## [1] 0.3700234

Question 8

Slightly correlated, positve correlation