# http://stat.ethz.ch/R-manual/R-patched/library/stats/html/fisher.test.html

# Creating matrix: cohesion familiarity vs. ratings

> cohFam_Ratings1 <- matrix(c(41,4,26,0, 4,0,4,1), nrow = 2, ncol = 4, byrow = TRUE, dimnames = list(c("Yes", "No"), c("1st more cohesive", "2nd more cohesive", "Equally coh", "Don't know")))

> cohFam_Ratings1
   1st more cohesive 2nd more cohesive Equally coh Don't know
Yes                41                 4          26          0
No                  4                 0           4          1

>cohFam_Ratings2 <- matrix(c(50,9,12,0, 4,1,3,1), nrow = 2, ncol = 4, byrow = TRUE, dimnames = list(c("Yes", "No"), c("1st more cohesive", "2nd more cohesive", "Equally coh", "Don't know")))

>cohFam_Ratings2
    1st more cohesive 2nd more cohesive Equally coh Don't know
Yes                50                 9          12          0
No                  4                 1           3          1
 
>cohFam_Ratings3 <- matrix(c(5,41,24,1, 1,2,6,0), nrow = 2, ncol = 4, byrow = TRUE, dimnames = list(c("Yes", "No"), c("1st more cohesive", "2nd more cohesive", "Equally coh", "Don't know")))

>cohFam_Ratings3
   1st more cohesive 2nd more cohesive Equally coh Don't know
Yes                 5                41          24          1
No                  1                 2           6          0


# Executing the Fisher exact test between Cohesion familiarity and Ratings

> fisher.test(cohFam_Ratings1, simulate.p.value = TRUE)

        Fisher's Exact Test for Count Data with simulated p-value (based on 2000 replicates)

data:  cohFam_Ratings1 
p-value = 0.1704
alternative hypothesis: two.sided 

> fisher.test(cohFam_Ratings1)

        Fisher's Exact Test for Count Data

data:  cohFam_Ratings1 
p-value = 0.1753
alternative hypothesis: two.sided 


> fisher.test(cohFam_Ratings2, simulate.p.value = TRUE)

        Fisher's Exact Test for Count Data with simulated p-value (based on 2000 replicates)

data:  cohFam_Ratings2 
p-value = 0.05447
alternative hypothesis: two.sided 

> fisher.test(cohFam_Ratings2)

        Fisher's Exact Test for Count Data

data:  cohFam_Ratings2 
p-value = 0.06224
alternative hypothesis: two.sided 


> fisher.test(cohFam_Ratings3, simulate.p.value = TRUE)

        Fisher's Exact Test for Count Data with simulated p-value (based on 2000 replicates)

data:  cohFam_Ratings3 
p-value = 0.1544
alternative hypothesis: two.sided 

> fisher.test(cohFam_Ratings3)

        Fisher's Exact Test for Count Data

data:  cohFam_Ratings3 
p-value = 0.1523
alternative hypothesis: two.sided