#X2 & G Tests for Association in RxC Contingency Tables
#Using the Sex of the Dog (R) by Coat Color (C) example data table
#Enter the RxC Contingency as a matrix:
X=matrix(c(158,200,46,46,170,282,51,47),nrow=2,byrow=T)
X
chisq.test(X)

#Calculate G Test Statistic, assigning O as observed and E as expected frequencies
O=matrix(chisq.test(X)$observed) 
O
E=matrix(chisq.test(X)$expected)
E
G=2*sum(O*log(O/E))
G

#Determine the Critical Value using the qchisq() function
#Set the Type 1 Error to alpha = 0.05
#Input the R = # Rows and C= # Columns to calculate the df
alpha=0.05
R=2
C=4
df=(R-1)*(C-1)
CV=qchisq(1-alpha,df)
CV

#Calculate the Probability for the G and X Test Statistic:
PG=(1-pchisq(G,df))
PG
Xsq=sum(((O-E)^2)/E)
PX=(1-pchisq(Xsq,df))
PX

#CREATE A RxC CONTINGENCY TABLE IN R FORMAT
#Upload and save the dataset MBML.RxC into your working directory
RxC=read.table("c:/R/MBML.RxC.txt")
RxC
attach(RxC)

#Use the table function and input the (Row, Column) categorical variables 
#Check the data with the chisq.test() function
T=table(Gender,Eye.Color)
T
chisq.test(T)