##########################
## CQS Summer Institute ##
##    Biostatistics 1   ##
##    Tatsuki Koyama    ##
##########################

## MouseWeight.xls has the data from an experiment. 
## Mouses 11~20 are in 'Uninfected' group, and mouses 21~30 are in 'Infected'
## group. 

## 1. Data cleaning ##
## This data sheet requires some cleaning. 

## First, we need this file as a .csv (text) file. Save it as
## 'MouseWeight.csv'. (Some of the information are lost.)

## Second, Mean and SD are not a part of the data. They do not belong here with
## the data. Delete them. 

## Third, each mouse needs 'Group' variable. Fill in the column. (There is an
## easy way to do this in R, but copy-pasting is ok for now.)

## Read in the data.
mouseWeight <- read.csv('MouseWeight.csv')

## Data summary.
## Let's get some summaries of the data.
## groupSum() function is useful. 
source('http://biostat.mc.vanderbilt.edu/wiki/pub/Main/TatsukiRcode/RFunctions071817.R')
groupSum(mouseWeight$Baseline, mouseWeight$Group)

## Let's look at the data. 
source('http://biostat.mc.vanderbilt.edu/wiki/pub/Main/TatsukiRcode/RFunctions0.R')
tplot(Baseline ~ Group, data=mouseWeight)
## Try different options...
tplot(Baseline ~ Group, data=mouseWeight, type='db', show.n=TRUE, ylim=c(10,18))
## What do you notice?

## Q1 Test whether the baseline weight is different (on average) between the groups.
## Write the hypotheses.
## What can you say?

## Q1 Test whether 'infected' mice, on average, lose more weight by Day 1. 
## Q1a. Write the hypotheses.
##
## Q1b. Create a column 'change1', which is weight change from Baseline to Day 1.
mouseWeight$change1 <- mouseWeight$Day1 - mouseWeight$Baseline

## Q1c. How about using the fold-change?
mouseWeight$foldChange1 <- mouseWeight$Day1 / mouseWeight$Baseline