chi_square

#install.packages("EnvStats")
#install.packages("readxl")

library(tidyverse)

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## ✖ 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

library(infer)
library(EnvStats)

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

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

chi4 <-  read.csv("Frequency_Chi_Square_4.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

chisq.test(chi4$Reading,chi4$English)

## 
##  Pearson's Chi-squared test
## 
## data:  chi4$Reading and chi4$English
## X-squared = 11.96, df = 12, p-value = 0.4489

chisq.test(chi4$C3, chi4$C4)

## 
##  Pearson's Chi-squared test
## 
## data:  chi4$C3 and chi4$C4
## X-squared = 11.631, df = 9, p-value = 0.2349

chisq.test(chi4$Reading,chi4$C3)

## 
##  Pearson's Chi-squared test
## 
## data:  chi4$Reading and chi4$C3
## X-squared = 780, df = 9, p-value < 2.2e-16

##tabulate(chi4$English, chi4$C4)

table (chi4$English)

## 
##     A  B  C  D 
## 40 49 53 56 62

table(chi4$English, chi4$C4)

##    
##      1  2  3  4
##      0  0  0  0
##   A 49  0  0  0
##   B  0 53  0  0
##   C  0  0 56  0
##   D  0  0  0 62

table(chi4$Reading, chi4$C3)

##    
##      1  2  3  4
##   A 66  0  0  0
##   B  0 66  0  0
##   C  0  0 60  0
##   D  0  0  0 68

chi4xl <- read_excel("Frequency_Chi_Square_4.XLSX")

table(chi4xl$Reading, chi4xl$C3)

##    
##      1  2  3  4
##   A 66  0  0  0
##   B  0 66  0  0
##   C  0  0 60  0
##   D  0  0  0 68