Report.Rmd

---
title: "Report"
author: "Gerhard Nachtmann"
date: "18 Oktober 2016"
output: html_document
---

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

## Section 1

### Demonstration of markdown features.

Section 2
=========

List

+ packages
    + markdown
    + knitr
    + ggplot2
+ output
    + pdf
    + HTML
    + word

1. packages
    1. rmarkdown
    1. knitr
    1. ggplot2
3. output
    1. pdf
    2. HTML
    2. word

This is Text. This word is **bold**. And here there is one printed in *italics*.

Underscores are also possible:

* __bold__
* _italics_ using underscores \_
* ~~strike~~
* standard

Links

https://github.com/nachti/ISPS16/

[ISPS Github Repository](https://github.com/nachti/ISPS16/)

```{r header, eval=TRUE, echo=FALSE}
library(ggplot2)
```


```{r iris}
data(iris)
head(iris)
```

### Just print the code, but don't evaluate it

```{r just_code, eval=FALSE}
summary(x)
## comment
```

### Just evaluate the code, but don't print it

```{r just_output, echo=FALSE}
summary(iris)
```

The iris dataset contains `r length(iris$Species)` observations of the `r nlevels(iris$Species)` species `r levels(iris$Species)`.

If `ggplot2` is not installed, write `install.packages(ggplot2, dep = TRUE)`.


## Including Plots

Visualize iris data.

```{r irisplot1, echo=FALSE}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, col = Species)) + geom_point() + geom_smooth()
```

```{r irisplot2, echo=FALSE}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, col = Species)) + geom_point() + geom_smooth(method="lm")
```

```{r irisplot3, echo=FALSE}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, col = Petal.Width)) + geom_point()
```

```{r irisplot4, echo=FALSE}
ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, col = Petal.Width)) + geom_point() + facet_wrap(~Species)
```