Data Science for Psychologists
A Refreshed Exploratory & Graphical Data Analysis in R
Welcome to class! This website is designed to accompany Mason Garrison’s Data Science for Psychologists (DS4P). DS4P is a graduate-level quantitative methods course at Wake Forest University. This class assumes zero knowledge of programming, computer science, linear algebra, probability, or really anything fancy. I encourage anyone who is quant-curious to work their way through these course notes. The course notes include lectures, worked examples, readings, activities, and labs. You can find the current version of the course syllabus here, along with all of the other syllabi for my classes. All the embedded lecture videos can be found on a youtube playlist.
This website is constantly changing. I am actively developing this course, and is approximately 91.9% done. I have made this process explicitly transparent because I want you to see how you can use R to produce some pretty neat things. Indeed, I’ve included the source code for this website in the class repo. I encourage you to contribute to the course code. If you catch typos or errors, please issue a pull request with the fixes. If you find cool or useful resources, please add them. By the end of the semester, I would love for everyone to have contributed to the course materials.
To navigate these course notes, use the table of contents on the left side of the screen. You can open or close the table of contents using the hamburger icon (horizontal bars) at the top of the document. There are also additional icons at the top of the document that allow you to search the document, change the size, font, or color scheme of the page. The document will be updated (unpredictably) throughout the semester.
Every module corresponds to a week’s worth of material. Most modules are dedicated to improving a specific skill or at the very least dedicated to a specific theme. Within each module, there are embedded videos, slides, activities, labs, and tutorials. The skills developed in each module build upon skills you’ve developed in previous modules. Eventually, this class will have more modules available than weeks in a semester, so that you – the reader – can choose your own adventure (err… module) you’d like to start with.
Although these notes have some textbook-like features, they are neither comprehensive nor completely original. The main purpose is to give you all a set of common materials to draw upon during the course. In class, we will sometimes do things outside the notes. The idea here is that you will read the materials and try to learn from them, just as you will attend classes and try to learn from them.
In terms of timing, I will have each module completed by the start of the week. Given that the class meets on Tuesday and Thursday, the start of the “week” will be Monday at 12 p.m. EST. I may get ahead of this deadline. You can see the current status of the course below. Although you are welcome to work ahead, be aware that I will be making changes to modules that haven’t officially started yet. In addition, I may add optional materials to previous modules that might be helpful.
This table provides the current status of the course. It lists proportions of specific components by module. Overall, it is 91.912% complete.