# Course Overview

## Schedule

Schedule

## Meetups

Meetups

## Textbooks

Required Diez, D.M., Barr, C.D., & Ã‡etinkaya-Rundel, M. (2019). OpenIntro Statistics (4th Ed). This is an open source textbook and can be downloaded in PDF format here, from the OpenIntro website, or a printed copy can be ordered from Amazon. Navarro, D. (2018, version 0.6). Learning Statistics with R This is free textbook that supplements a lot of the material covered in Diez and Barr. We will use the chapter on Bayesian analysis.

## Software

R and RStudio We will make use of R, an open source statistics program and language. Be sure to install R and RStudio on your own computers within the first few days of the class. R - Windows or Mac RStudio - Download Windows or Mac version from here If using Windows, you also need to download RTools and ActivePerl. LaTeX LaTeX is a typesetting language for preparing documents.

## Links

These are some useful resources on the web for learning R. Feel free to suggest other resources by clicking the “Improve this page” button in the top right. Learning R R for Data Science. Book by Garrett Grolemund and Hadley Wickham Quick-R. Kabakoff’s website. Great reference along with his book, R in Action. O’Reilly Try R. Great tutorial on R where you can try R commands directly from the web browser.

## Math Equations

Occasionally you will need to type equations in homework and labs. R Markdown supports LaTeX style equations using the MathJax javascript library. I do not expect you to learn LaTeX for this course. Instead, I recommend using the free application [Daum Equation Editor](). It availabe online, as a Google Chrome Extension, or as a standalone Mac Application. Creating Equations with Daum Equation Editor Occasionally you will need to type equations in homework and labs.

## Materials

Materials