hw 5

library(tidyverse)

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library(readxl)
library(dplyr)
library(pastecs)

## 
## Attaching package: 'pastecs'
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## The following objects are masked from 'package:dplyr':
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##     extract

read_excel("district.xls")

## # A tibble: 1,207 × 137
##    DISTNAME         DISTRICT DZCNTYNM REGION DZRATING DZCAMPUS DPETALLC DPETBLAP
##    <chr>            <chr>    <chr>    <chr>  <chr>       <dbl>    <dbl>    <dbl>
##  1 CAYUGA ISD       001902   001 AND… 07     A               3      574      4.4
##  2 ELKHART ISD      001903   001 AND… 07     A               4     1150      4  
##  3 FRANKSTON ISD    001904   001 AND… 07     A               3      808      8.5
##  4 NECHES ISD       001906   001 AND… 07     A               2      342      8.2
##  5 PALESTINE ISD    001907   001 AND… 07     B               6     3360     25.1
##  6 WESTWOOD ISD     001908   001 AND… 07     B               4     1332     19.7
##  7 SLOCUM ISD       001909   001 AND… 07     B               2      361      0.3
##  8 ANDREWS ISD      002901   002 AND… 18     B               6     4131      0.8
##  9 PINEYWOODS COMM… 003801   003 ANG… 07     A               4      995     15.7
## 10 HUDSON ISD       003902   003 ANG… 07     A               5     2799      7.2
## # ℹ 1,197 more rows
## # ℹ 129 more variables: DPETHISP <dbl>, DPETWHIP <dbl>, DPETINDP <dbl>,
## #   DPETASIP <dbl>, DPETPCIP <dbl>, DPETTWOP <dbl>, DPETECOP <dbl>,
## #   DPETLEPP <dbl>, DPETSPEP <dbl>, DPETBILP <dbl>, DPETVOCP <dbl>,
## #   DPETGIFP <dbl>, DA0AT21R <dbl>, DA0912DR21R <dbl>, DAGC4X21R <dbl>,
## #   DAGC5X20R <dbl>, DAGC6X19R <dbl>, DA0GR21N <dbl>, DA0GS21N <dbl>,
## #   DDA00A001S22R <dbl>, DDA00A001222R <dbl>, DDA00A001322R <dbl>, …

district <- read_excel("district.xls")

cor(district$DA0912DR21R, district$DA0AT21R, use = "complete.obs")

## [1] -0.3991648

pairs( district[, c("DA0912DR21R", "DA0AT21R")] )

cor.test(district$DA0912DR21R, district$DA0AT21R, use = "complete.obs")

## 
##  Pearson's product-moment correlation
## 
## data:  district$DA0912DR21R and district$DA0AT21R
## t = -14.393, df = 1093, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  -0.447817 -0.348156
## sample estimates:
##        cor 
## -0.3991648

I chose the pearson test because it was the one of the three I understood the most. I can say that by looking at this test that there is a negative correlation of almost -.4 which is still a correlation. This means that these two variables do have something to do with each other. They basically mean that when one goes up, the other goes down.