---
title: "Rock fries your brains 3"
author: ""
date: ""
output:
  html_document:
    fig_height: 3
    fig_width: 5
  pdf_document:
    fig_height: 3
    fig_width: 5
  word_document:
    fig_height: 3
    fig_width: 5
---

```{r, setup, include=FALSE}
require(mosaic)   # Load additional packages here 

# Some customization.  You can alter or delete as desired (if you know what you are doing).
trellis.par.set(theme=theme.mosaic()) # change default color scheme for lattice
knitr::opts_chunk$set(
  tidy=FALSE,     # display code as typed
  size="small")   # slightly smaller font for code
```

## The data

To read more about the dataset and see an explorative analysis have a look at the Rmarkdown file `rock-fries-your-brains.Rmd` in the exercises for the first lecture.

### Load data
In the data, missing values are coded as 999 (but this is handled by the command 
below that replace 999 by NA). Loading data:

```{r}
musik <- read.delim("https://asta.math.aau.dk/datasets?file=musik.txt", na.strings = "999")
```

## Mozart versus control group

We will compare the control group with the Mozart group, i.e. we leave
out the Anthrax group (group=3):
```{r}
noAnthrax <- subset(musik, group < 3)
```
Now we have a new dataset called `noAnthrax` which we will use in the remainder.
First change the group variable into a factor with sensible names:
```{r}
noAnthrax$group <- factor(noAnthrax$group, labels = c("control", "Mozart"))
```

### Median time week 1

Consider the response variable `median1` and compare it for the control and Mozart groups.
I.e. use a $t$-test to investigate whether the mean resoponse is different for the two groups. To do this you need to insert a new code chunk and write something like `t.test(response var. ~ grouping var. , data = ???)` with appropriate changes on your own:

Supplement this analysis with a boxplot:
```{r}
# Delete this and write something like gf_boxplot(??? ~ ??? , data = ???)
```

### Median time week 4

Make a similar analysis for `median4`

## Paired test for control group

We now only consider the control group and the response `median` for this group.
It is measured in week1 (`median1`) and week4 (`median4`) and we make a simple
dataset where we stack the median values from week 1 and week 4 on top of each other. The column `values` contains the values (median time) and the column `ind` is an indicator of week 1 or 4 (it is always good to have a look at the first few lines of the dataset with the function `head`):
```{r}
control <- subset(noAnthrax, group == "control")
median14 <- stack(na.omit(control), c(median1, median4))
head(median14)
```

Make a comparative analysis of the median from week1 to week4:
```{r}
favstats(values ~ ind, data = median14)
gf_boxplot(values ~ ind, data = median14)
t.test(values ~ ind, data = median14, paired = TRUE)
```