# Notes for Grad Student Orientation 2018

*Charles J. Geyer*

# 1 Introduction

These are some notes for grad student orientation in the School of Statistics, University of Minnesota, Fall 2018.

## 1.1 License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (http://creativecommons.org/licenses/by-sa/4.0/).

## 1.2 R

The version of R used to make this document is 3.5.1.

The version of the

`bookdown`

package used to make this document is 0.7.The version of the

`rmarkdown`

package used to make this document is 1.10.The version of the

`knitr`

package used to make this document is 1.20.The version of the

`ggplot2`

package used to make this document is 3.0.0.

## 1.3 Other Learning Materials

### 1.3.1 An Introduction to R

By far the best book on R is free, written by the R core team, always up to date with the current version, and always correct. It is called *An Introduction to R* and can be found in your R distribution. Do

`help.start()`

to start browser help and click on the “An Introduction to R” link.

If can also be found on-line at CRAN.

PDF and e-book versions are also available at CRAN.

On the web page `help.start()`

gives you or at the link just above you see there are also five other manuals that come with R, but they are for experts. You don’t want to read them yet.

### 1.3.2 An R Short Course

Your humble author was one of five instructors for a two-day short course on R. Here are the notes for it.

### 1.3.3 An R Course (Undergraduate)

Your humble author taught Stat 3701 (undergraduate statistical computing). Here is the web site for that.

Of particular interest are the

### 1.3.4 An R Course (PhD Level)

Your humble author taught Stat 8054 (PhD level statistical computing). Here is the web site for that.

That site is a bit out of date. I will redo it when I teach that course again in Spring 2019, including many topics from my Stat 3701 notes linked above, like web scraping, JSON, and SQL databases. And I will update many topics, like parallel computing.