chi_square

#install.packages("EnvStats")

library(tidyverse)

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library(infer)
library(EnvStats)

## 
## Attaching package: 'EnvStats'
## 
## The following objects are masked from 'package:stats':
## 
##     predict, predict.lm
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## The following object is masked from 'package:base':
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##     print.default

chi <- read.csv("Frequency_Chi_Square.csv")

chisq.test(chi$Reading, chi$English, correct = FALSE)

## 
##  Pearson's Chi-squared test
## 
## data:  chi$Reading and chi$English
## X-squared = 11.96, df = 12, p-value = 0.4489

#chisq.test(chi$Reading)

x <- c(10.4, 8.6, 8.0, 3.4, 3);
chisq.test(x)

## 
##  Chi-squared test for given probabilities
## 
## data:  x
## X-squared = 6.5222, df = 4, p-value = 0.1634

chin <- read.csv("Frequency_Chi_Square_Numeric.csv")

chisq.test(chin$C3)

## Warning in chisq.test(chin$C3): Chi-squared approximation may be incorrect

## 
##  Chi-squared test for given probabilities
## 
## data:  chin$C3
## X-squared = 133.2, df = 259, p-value = 1

chisq.test (chin$Reading, chin$C3)

## 
##  Pearson's Chi-squared test
## 
## data:  chin$Reading and chin$C3
## X-squared = 780, df = 9, p-value < 2.2e-16

chisq.test (chin$Reading,chin$English)

## 
##  Pearson's Chi-squared test
## 
## data:  chin$Reading and chin$English
## X-squared = 11.96, df = 12, p-value = 0.4489

chisq.test (chin$English, chin$C3)

## 
##  Pearson's Chi-squared test
## 
## data:  chin$English and chin$C3
## X-squared = 11.96, df = 12, p-value = 0.4489