This course is the first in a 3-term sequence of classes designed to provide a thorough grounding in statistical concepts, methods, and applications of relevance to psychological science and related sciences. The aim of the course is to help students develop skills in the analysis and interpretation of real psychological data. Our focus will be both conceputual and mathematical – that is, understanding the underlying mathematical principals of statistics enhances ones’ ability to interpret and think critically about the use of statistics. Students will also learn the basics of the R language and use this program to wrangle, visualize, summarize, and test hypotheses with data.
Lecture: Tuesdays and Thursdays, 10 - 11:20am, McKenzie Hall Rm 121
Lab: Friday, 9-10:20am or 10:30-11:50am, Straub Hall Rm 008
Sara Weston – sweston2@uoregon.edu Office Hours: Thursday 11:30am-1:30pm, Straub 325
Cameron Kay – ckay@uoregon.edu Office Hours: Monday 12:10pm-2:10pm, Straub 461
Brendan Cullen – bcullen@uoregon.edu Office Hours: Tuesday 2-4pm, LISB 229
We will primarily be referring to chapters in Learning Statistics with R by Danielle Navarro. This textbook is available for free online. You may choose to purchase a paper copy if you wish, but it is not required. Additional readings assignments will be posted here.
Students must have the latest version of R, which can be downloaded here. It is strongly recommended that students also download the RStudio GUI, available here. Both softwares are free.
While we will be covering the use of R and RStudio extensively in both lecture and lab, one of the key skills required to use R is the ability to find answers on the Internet. The R commmunity (sometimes referred to as the useR community) tends to be friendly and helpful and enjoys solving R-related problems in their spare time. For that reason, many common questions or problems have been posted to spaces online and answered by smart people. Finding and deciphering those answers is the key skill you should seek to hone this year. It’s much more important than remembering function names.
Here are some sites where you can find the answers to many R questions and learn new tricks: