create an Rmarkdown document with “district” data

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.2.1     ✔ readr     2.2.0
## ✔ forcats   1.0.1     ✔ stringr   1.6.0
## ✔ ggplot2   4.0.3     ✔ tibble    3.3.1
## ✔ lubridate 1.9.5     ✔ tidyr     1.3.2
## ✔ purrr     1.2.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readxl)



district<-read_excel("district.xls")

create a new data frame with “DISTNAME”, “DPETSPEP” (percent special education) and “DPFPASPEP” (money spent on special education). call the dataframe whatever you want

data1<-district %>% select(DISTNAME,DPETSPEP,DPFPASPEP)

give me “summary()” statistics for both DPETSPEP and DFPASPEP. You can summarize them separately if you want.

summary(data1)
##       DISTNAME       DPETSPEP       DPFPASPEP     
##  Length   :1207   Min.   : 0.00   Min.   : 0.000  
##  N.unique :1196   1st Qu.: 9.90   1st Qu.: 5.800  
##  N.blank  :   0   Median :12.10   Median : 8.900  
##  Min.nchar:   7   Mean   :12.27   Mean   : 9.711  
##  Max.nchar:  50   3rd Qu.:14.20   3rd Qu.:12.500  
##                   Max.   :51.70   Max.   :49.000  
##                                   NAs    :5

Which variable has missing values?

The missing values are in DPFPASPEP - there are 5 missing values

remove the missing observations. How many are left overall? (REMOVE WITH drop_na)

data2<-data1 %>% na.omit()

There are 1,102 observations remaining in Data2

cor(data2$DPFPASPEP,data2$DPETSPEP)
## [1] 0.3700234

There is a weak correlation between the districts spending on special education versus the percentage of students in special education.