#Load table into a new object "Awake" and attach it to the workspace
Death<- read.table("C:/Users/Challenger/Documents/Stats/TEA_flies_deaths1.txt",
                   header = TRUE, stringsAsFactors = TRUE)
attach(Death)

#Define variables
dead<- Deaths
anesthesia<-Treatment
sex <- Sex

#Checking the variables
summary(dead)
summary(sex)
summary(anesthesia)

#Test of normality, significant result = non-normal
shapiro.test(dead)

#plotting the residuals
qqnorm(dead)

#general linear model with poisson regression for count data
dead.glm <- glm(dead ~anesthesia+sex, family = poisson)
summary(dead.glm)
dead.glm2 <- glm(dead~anesthesia, family = poisson)
summary(dead.glm2)
dead.glm3 <- glm(dead ~anesthesia*sex, family = poisson)
summary(dead.glm)

dead.glm4 <- glm(dead~anesthesia, family = quasipoisson)
summary(dead.glm4)

anova(dead.glm, dead.glm3, test="Chi")
anova(dead.glm, dead.glm2, test="Chi")

#creates table with response variable and significant variable
tapply(dead,list(anesthesia),mean)

#package for multiple comparisons
install.packages("multcomp")
library("multcomp")

#run multiple comparisons
summary(glht(dead.glm2, mcp(anesthesia="Tukey")))

#creates bargraph of response variable (deaths)
barplot(tapply(dead,list(anesthesia),mean))