######################################
#Load the data 
setwd("E:\\Documents\\Entropy Loot")

data=read.csv("EntropyLoot_v2.csv")

boxplot(good.loot~ID.class,data, ylab="Number of Good Loops")     


#Perform the unpaired two-sample t test
#Check assumptions
#Are samples independent?
#yes they were collected independently from raiding each week

#Are data from each group normally distributed 
with(data, shapiro.test(good.loot[ID.class=="Jrueg"])) #p-val=0.32 #We don't reject Null = yes normally distributed
with(data, shapiro.test(good.loot[ID.class=="Random"])) #p-val=0.85 #We don't reject Null = yes normally distributed

#Do the two populations have the same variance?
var.test(good.loot~ID.class, data = data) #p-val=0.25 ##We don't reject Null = yes equal variance

our.test=t.test(good.loot~ID.class, data = data, var.equal = TRUE)
our.test
#p-val=0.18 = we fail to reject the null hypothesis

#Other Stats
#SD - standard deviation
with(data, sd(good.loot[ID.class=="Jrueg"])) 
with(data, sd(good.loot[ID.class=="Random"]))