setwd("C:/YU/teaching/致远交叉创新/data/")


##One-sample T-test Q16 in Chapter10
heart<-read.csv("heart.csv",header=TRUE)
t.test(heart$pdi,mu=100,alternative = "two.sided" )

##Two-sample t-test low birth weight data
lowbwt<-read.csv("lowbwt.csv",header=TRUE)
sbp_male<-lowbwt$sbp[which(lowbwt$sex==1)]
sbp_female<-lowbwt$sbp[which(lowbwt$sex==0)]
t.test(sbp_male,sbp_female,alternative = "two.sided" )

t.test(lowbwt$sbp~lowbwt$sex,alternative = "two.sided" )

##One-way ANOVA lung function example
pulmonary_function<-read.csv("pulmonary function.csv",header=TRUE)
fev1<- as.numeric(as.character(pulmonary_function$fev1))
center<-as.factor(pulmonary_function$center)
fev.aov<-aov(fev1~center)
fev.aov
summary(fev.aov)

##Multiple comparison week8.fevl
TukeyHSD(fev.aov,conf.level = 0.9)


##Two way ANOVA
rm(list = ls())
weight = read.table('Exe_Diet_Weight.txt', header = T, sep = "\t")
attach(weight)
Exercise = as.factor(Exercise)
Diet = as.factor(Diet)
aggregate(weight, by = list(Exercise), FUN = mean)
aggregate(weight, by = list(Exercise), FUN = sd)
aggregate(weight, by = list(Diet), FUN = mean)
aggregate(weight, by = list(Diet), FUN = sd)
fit  = aov(Response ~ Exercise + Diet + Exercise*Diet)
summary(fit)
detach(weight)

##Kruskal Wallis One-way ANOVA
rm(list = ls())
hospital = read.table('hospital.txt', header = T, sep = "\t")
hospital
kanova=kruskal.test(hospital)
##Friedman Two-Way ANOVA
rm(list = ls())
drug = read.table('drug.txt', header = T, sep = "\t")
drug
friedman.test(FEV_change ~ Drug | Patient, data = drug)