This is a quick set of analyses of the California Test Score dataset. The post was produced using R Markdown in RStudio 0.96. The main purpose of this post is to provide a case study of using R Markdown to prepare a quick reproducible report. It provides examples of using plots, output, in-line R code, and markdown. The post is designed to be read along side the R Markdown source code, which is available as a gist on github.

## Friday, May 18, 2012

## Thursday, May 17, 2012

### Getting Started with R Markdown, knitr, and Rstudio 0.96

This post examines the features of R Markdown
using knitr in Rstudio 0.96.
This combination of tools provides an exciting improvement in usability for
reproducible analysis.
Specifically, this post
(1) discusses getting started with R Markdown and `knitr`

in Rstudio 0.96;
(2) provides a basic example of producing console output and plots using R Markdown;
(3) highlights several code chunk options such as caching and controlling how input and output is displayed;
(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and
(5) discusses the implications of R Markdown.
This post was produced with R Markdown. The source code is available here as a gist.
The post may be most useful if the source code and displayed post are viewed side by side.
In some instances, I include a copy of the R Markdown in the displayed HTML, but most of the time I assume you are reading the source and post side by side.

## Thursday, May 3, 2012

### How to plot three categorical variables and one continuous variable using ggplot2

This post shows how to produce a plot involving three categorical variables
and one continuous variable using `ggplot2`

in R.