#?ToothGrowth
#The response is the length of odontoblasts (cells responsible for tooth growth) in 60 guinea pigs. Each animal received one of three dose levels of vitamin C (0.5, 1, and 2 mg/day) by one of two delivery methods, orange juice or ascorbic acid (a form of vitamin C and coded as VC).
data("ToothGrowth")
head(ToothGrowth)
## len supp dose
## 1 4.2 VC 0.5
## 2 11.5 VC 0.5
## 3 7.3 VC 0.5
## 4 5.8 VC 0.5
## 5 6.4 VC 0.5
## 6 10.0 VC 0.5
summary(ToothGrowth)
## len supp dose
## Min. : 4.20 OJ:30 Min. :0.500
## 1st Qu.:13.07 VC:30 1st Qu.:0.500
## Median :19.25 Median :1.000
## Mean :18.81 Mean :1.167
## 3rd Qu.:25.27 3rd Qu.:2.000
## Max. :33.90 Max. :2.000
# make dose as a factor has three levels
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
#plot teeth length ~ dose level by supplement type
library("ggplot2")
ggplot(ToothGrowth, aes(x=dose, y=len, fill=supp))+
geom_boxplot()+
facet_grid(.~supp)
#plot teeth length ~ supplement type by dose level
ggplot(ToothGrowth, aes(x=supp, y=len, fill=supp))+
geom_boxplot()+
facet_grid(.~dose)
Use hypothesis tests to compare tooth growth by supp and dose
t.test(len ~ supp, data = ToothGrowth)
##
## Welch Two Sample t-test
##
## data: len by supp
## t = 1.9153, df = 55.309, p-value = 0.06063
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -0.1710156 7.5710156
## sample estimates:
## mean in group OJ mean in group VC
## 20.66333 16.96333
#T test at dose level 0.5
dose1 <- subset(ToothGrowth, dose %in% c(0.5) )
t.test(len ~ supp, data = dose1)
##
## Welch Two Sample t-test
##
## data: len by supp
## t = 3.1697, df = 14.969, p-value = 0.006359
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 1.719057 8.780943
## sample estimates:
## mean in group OJ mean in group VC
## 13.23 7.98
#T test at dose level 0.1
dose1 <- subset(ToothGrowth, dose %in% c(1.0) )
t.test(len ~ supp, data = dose1)
##
## Welch Two Sample t-test
##
## data: len by supp
## t = 4.0328, df = 15.358, p-value = 0.001038
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## 2.802148 9.057852
## sample estimates:
## mean in group OJ mean in group VC
## 22.70 16.77
#T test at dose level 2
dose1 <- subset(ToothGrowth, dose %in% c(2.0) )
t.test(len ~ supp, data = dose1)
##
## Welch Two Sample t-test
##
## data: len by supp
## t = -0.046136, df = 14.04, p-value = 0.9639
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -3.79807 3.63807
## sample estimates:
## mean in group OJ mean in group VC
## 26.06 26.14