# KnitR/diceIndependent.Rmd

```---
title: "Checking for independence - a simple KnitR example"
author: "Martin Papke"
date: "23 August 2018"
output: pdf_document
---

```{r setup, include=FALSE}
knitr::opts_chunk\$set(echo = TRUE)
library(knitr)
```

# A simple KnitR example

## Data import

In this document we aim to show how KnitR can be used to gerenate a report or an article
containing statistical data and how the R code can be integrated within the document.
As example data, we use 10000 dice rolls contained in the file *dice.csv*. As usual in R
we can load the data with
# dice <- as.numeric(data\$X3)
```
To give a standalone example here, we use R's feature to generate random numbers
```
dice <- sample(1:6, 10000, replace=TRUE)
```

### Preperation of the data
As we want to use the dice throws in pairs, we just generate a table comparing the even and the odd dice throws,
this can be done as follows:
```{r dataprep}
even <- dice[seq.int(0,10000,2)]
odd  <- dice[seq.int(1,10000,2)]
tbl  <- table(even, odd)
```
We obtain the results
```{r table1, echo=FALSE}
kable(tbl, caption='even and odd results compared')
```

## Statistics

No we check for independence, by invoking
```{r chisquared}
chi <- test.chisq(tbl)
p   <- chi\$p.value
```
The \$p\$-value is `r p`. Hence, we can say that we have
```{r pvalue}
if (p < 0.01) {
"high significance for independene"
} else if (p < 0.05) {
"significance for independence"
} else {
"no significance for independence"
}
```
```