The Normal Distribution
=======================
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The normal (or Gaussian) distribution is defined as follows:
$$latex
f(x;\mu,\sigma^2) = \frac{1}{\sigma\sqrt{2\pi}}
e^{ -\frac{1}{2}\left(\frac{x-\mu}{\sigma}\right)^2 }
$$
To generate random draws from a normal distribution we use the **rnorm** function:
```{r block1}
output <- rnorm(1000, 100, 15);
```
The normal distribution has the typical bell shape:
```{r block2, fig.width=8, fig.height=5}
library(ggplot2)
qplot(output)
```
## Kernel density estimation
We can perform density estimation on the sample:
```{r block3, fig.width=8, fig.height=5}
plot(density(output))
```
## Carl Friedrich Gauß
This little guy had something to do with it
!['Gauss'](https://goo.gl/eXN77h)