getwd()
rp <-"C:/Users/hp/Desktop/bayili passing"
setwd(rp)
readLines("dawa.txt",n=5)
dw <- read.table("dawa.txt",header=T,dec=",",sep="\t")
View(dw)
dput(colnames(dw))
str(dw)




######## Unwashing ########
Udw <- subset(dw,Number.of.washing==0)
dim(Udw)
plot(Udw$Mortality.rate.after.24h~Udw$treat)

tapply(Udw$Mortality.rate.after.24h,Udw$treat,median)
Kt<-kruskal.test(Udw$Mortality.rate.after.24h~Udw$treat, data=Udw)
Kt
#quel se manifeste les difference nous devons realiser#
#le teste de comparaison multiple#

#### ANOVA #####
mon<-lm(Udw$Mortality.rate.after.24h~Udw$treat)
summary(mon)
drop1(mon,.~.,test="F")
summary(mon)
hist(resid(mon),col="brown",main = "Mortality Rate\n after 24 hours")
bartlett.test(Udw$Mortality.rate.after.24h~Udw$treat)
pairwise.t.test(Udw$Mortality.rate.after.24h,Udw$treat,p.adjust.method="bonferroni")
mon.aov<-aov(Udw$Mortality.rate.after.24h~Udw$treat)
te<-TukeyHSD(mon.aov)
par(las=1,cex=0.75)
plot(te)
####### blood feeding ######
blfd<-lm(Udw$Blood.feeding.inhibition~Udw$treat)
summary(blfd)
drop1(blfd,.~.,test="F")
hist(resid(blfd),col="brown",main = "blood feding inihibition Rate\n after 24 hours")
bartlett.test(Udw$Blood.feeding.inhibition~Udw$treat)
mon.aov1<-aov(Udw$Blood.feeding.inhibition~Udw$treat)
te<-TukeyHSD(mon.aov1)
par(las=1,cex=0.75)
plot(te)
###### intervalle de confiance passing rate ####
#### confidente interval ######
require(binom)
total.tested<-by(Udw$Nb.mosquitoes.tested,Udw$treat,sum)
tot.test<-c(total.tested)
## Total des moustique mort par traitement##
tot.pass<- by(Udw$Number.passing.through.holes.in14h,Udw$treat,sum)
tot.p<-c(tot.pass)
# interval de confiance a 95% d'une proportion###
ci<-binom.confint(tot.p,tot.test,method="exact")
ci

write.table(ci,"Ci.exiting.txt",row.names=F,sep="\t",dec=",")
##### blood fef dead interval de confiance###
total.tested<-by(Udw$Nb.mosquitoes.tested,Udw$treat,sum)
tot.test<-c(total.tested)
## Total des moustique mort par traitement##
tot.bloodfed<- by(Udw$Number.of.blood.fed,Udw$treat,sum)
tot.b<-c(tot.bloodfed)
# interval de confiance a 95% d'une proportion###
ci<-binom.confint(tot.b,tot.test,method="exact")
ci

write.table(ci,"Ci.blood feed.txt",row.names=F,sep="\t",dec=",")




############### washing dawa ###################
## Mortality ##
Kt<-kruskal.test(Wdw$Mortality.rate.after.24h~Wdw$treat, data=Wdw)
Kt
require(coin)
pairwise.wilcox.test(Wdw$Mortality.rate.after.24h,Wdw$treat,p.adjust.method="bonferroni")
mon<-lm(Wdw$Mortality.rate.after.24h~Wdw$treat)
summary(mon)
drop1(mon,.~.,test="F")
summary(mon)
hist(resid(mon),col="brown",main = "Mortality Rate\n after 24 hours")
bartlett.test(Wdw$Mortality.rate.after.24h~Wdw$treat)
pairwise.t.test(Wdw$Mortality.rate.after.24h,Wdw$treat,p.adjust.method="bonferroni")
mon.aov<-aov(Udw$Mortality.rate.after.24h~Udw$treat)
te<-TukeyHSD(mon.aov)
par(las=1,cex=0.75)
plot(te)
## Blood feding ##

Kt<-kruskal.test(Wdw$Blood.feeding.inhibition~Wdw$treat, data=Wdw)
Kt
mon<-lm(Wdw$Blood.feeding.inhibition~Wdw$treat)
summary(mon)
drop1(mon,.~.,test="F")
summary(mon)
hist(resid(mon),col="brown",main = "Blood.feding inihibition\n after 24 hours")
bartlett.test(Wdw$Blood.feeding.inhibition~Wdw$treat)
pairwise.t.test(Wdw$Blood.feeding.inhibition,Wdw$treat,p.adjust.method="bonferroni")
mon.aov<-aov(Wdw$Blood.feeding.inhibition~Wdw$treat)
te<-TukeyHSD(mon.aov)
par(las=1,cex=0.75)
plot(te)
require(binom)
total.tested<-by(Wdw$Nb.mosquitoes.tested,Wdw$treat,sum)
tot.test<-c(total.tested)

## Total des moustique mort par traitement##
tot.pass<- by(Wdw$Number.passing.through.holes.in14h,Wdw$treat,sum)
tot.p<-c(tot.pass)
# interval de confiance a 95% d'une proportion###
ci<-binom.confint(tot.p,tot.test,method="exact")
ci

write.table(ci,"Ci.washingpassing.txt",row.names=F,sep="\t",dec=",")
##### blood fef dead interval de confiance###
total.tested<-by(Wdw$Nb.mosquitoes.tested,Wdw$treat,sum)
tot.test<-c(total.tested)
## Total des moustique mort par traitement##
tot.bloodfed<- by(Wdw$Number.of.blood.fed,Wdw$treat,sum)
tot.b<-c(tot.bloodfed)
# interval de confiance a 95% d'une proportion###
ci<-binom.confint(tot.b,tot.test,method="exact")
ci

write.table(ci,"Ci.blood washing.txt",row.names=F,sep="\t",dec=",")







###################################################
"Date"
"Treatment"
"Number.of.washing"
"Nb.mosquitoes.tested",
"Replicate"
"Number.passing.through.holes.in14h"
"Passing.rate"
"Number.of.blood.fed"
"Blood.fed.rate"
"Total.number.dead.after.24.h"
"Mortality.rate.after.24h"
"X.Blood.feeding.inhibition"
####################################################
grp <- plot(dw$Mortality.rate.after.24h~dw$Treatment)
tapply(dw$Mortality.rate.after.24h,dw$Treatment,summary)
mon<-lm(dw$Mortality.rate.after.24h~dw$Treatment)
summary(mon)
te<-TukeyHSD(mon)
par(las=1,cex=0.75)
plot(te)

##################################################
mon1<-aov(dw$X.Blood.feeding.inhibition~dw$Treatment)
te<-TukeyHSD(mon1)
par(las=1,cex=0.75)
plot(te)
pairwise.t.test(dw$X.Blood.feeding.inhibition,dw$Treatment,p.adjust.method="bonferroni")
tapply(dw$X.Blood.feeding.inhibition,dw$Treatment,median)
Kt<-kruskal.test(dw$X.Blood.feeding.inhibition~dw$Treatment, data=dw)
Kt
#quel se manifeste les difference nous devons realiser#
#le teste de comparaison multiple#
require(coin)
pairwise.wilcox.test(dw$X.Blood.feeding.inhibition,dw$Treatment,p.adjust.method="bonferroni")

















####### Krustal wallis test non parametrique #####
tapply(dw$Mortality.rate.after.24h,dw$Treatment,median)
Kt<-kruskal.test(dw$Mortality.rate.after.24h~dw$Treatment, data=dw)
Kt
#quel se manifeste les difference nous devons realiser#
#le teste de comparaison multiple#
require(coin)
pairwise.t.test(dw$Mortality.rate.after.24h,dw$Treatment,p.adjust.method="bonferroni")