Course Overview
Schedule
Schedule
Meetups
Meetups
Textbooks
Required Diez, D.M., Barr, C.D., & Çetinkaya-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.