Overview

The report aims to analyze the ToothGrowth data in the R datasets package.

library(knitr)
# Setting the global options.
opts_chunk$set(fig.width=6, fig.height=4, warning=FALSE)

Load the ToothGrowth data and perform some basic exploratory data analyses.

library(datasets)
data(ToothGrowth)
# Print the frame details
str(ToothGrowth)
## 'data.frame':    60 obs. of  3 variables:
##  $ len : num  4.2 11.5 7.3 5.8 6.4 10 11.2 11.2 5.2 7 ...
##  $ supp: Factor w/ 2 levels "OJ","VC": 2 2 2 2 2 2 2 2 2 2 ...
##  $ dose: num  0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 ...
unique(ToothGrowth$len); unique(ToothGrowth$dose)
##  [1]  4.2 11.5  7.3  5.8  6.4 10.0 11.2  5.2  7.0 16.5 15.2 17.3 22.5 13.6
## [15] 14.5 18.8 15.5 23.6 18.5 33.9 25.5 26.4 32.5 26.7 21.5 23.3 29.5 17.6
## [29]  9.7  8.2  9.4 19.7 20.0 25.2 25.8 21.2 27.3 22.4 24.5 24.8 30.9 29.4
## [43] 23.0
## [1] 0.5 1.0 2.0
library(ggplot2)
m <- ggplot(ToothGrowth, aes(x=factor(dose), y=len))
m + geom_boxplot() + facet_grid(.~supp) + ggtitle("ToothGrowth data details")

Provide a basic summary of the data.

Included figures highlight the means we are comparing.

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

Use confidence intervals and/or hypothesis tests to compare tooth growth by supp and dose.

# TBD

State your conclusions and the assumptions needed for your conclusions

Based on the visual inspection of data from the box plot; there is a direct relationship between the size of the tooth and the dose required for the same.