How to Read This Site
Welcome. Almost everything for this course lives on this website — the modules you read, the pre-study you work through, what happens in lecture, and the labs where you write code. It is a lot of material, and it is designed to be worked through a week at a time rather than searched.
A few small conventions run through all of it, and they exist to save you effort. The color of a box tells you what it is asking of you before you read a word: something to remember, something to try yourself, something you may skip without guilt, or something to talk through with the person sitting next to you. The colored code text does the same job in miniature, so you can tell a function from a dataset from a variable at a glance.
Callout Boxes
Seven types of callout box appear across the course materials — modules, labs, and lectures. Each has a distinct color so you can tell at a glance what kind of content it contains.
Core concepts and key takeaways. When you see a summary box, you are looking at a distillation of the most important ideas in the section — definitions, rules, or formulas you will want to be able to recall.
Supplementary depth. Every one of these indigo boxes carries a small label at its top — usually Going further, or More practice when the box is extra drilling on a skill you already have. They go beyond the core material — mathematical derivations, edge cases, extra context, or connections to more advanced methods. They enrich your understanding, but the main thread of each module stands without them, and nothing in them is required for the assessments. Read the ones that interest you; skip the rest without worry.
Self-assessment questions. These are worth sitting with for a moment before you move on. If an answer doesn't come easily, that's a cue to revisit the section — not a setback, just the material telling you where to spend a few more minutes. They also preview what you'll be thinking through in lecture and lab.
Copy-paste reporting templates. These boxes show exactly how to write up a statistical result in APA style, with inline R expressions that automatically fill in the correct numbers. Use these as templates for your own write-ups.
Dataset descriptions. Each module introduces the dataset it uses. The dataset box tells you where the data come from, what the rows and columns represent, and what question we will use it to investigate.
A whole-class moment. A cue — mostly in labs and lectures — to look up from your screen and work through something together: a shared activity, a demonstration, or a discussion worth having as a group. When one appears, it's an invitation to shift from reading to joining in.
A moment to think together. A short prompt — usually 30 seconds to two minutes — to turn to the person next to you, compare answers, and reason through a question aloud. Saying it out loud almost always clarifies something the reading left fuzzy.
Inline Styling
Throughout the text, different kinds of R objects are styled with distinct colors and backgrounds so you can immediately see what type of thing is being discussed.
| Style | Example | Meaning |
|---|---|---|
| teal mono | mean() | R function name |
| rose mono | tidyverse | R package name |
| indigo mono | lower.tail | Function argument name |
| heather mono | neg_sentiment | Variable (column) name |
| gold mono | fake_news | Data frame name |
| gray pill | factor | Variable type (factor, numeric, character) |
The Weekly Rhythm
Each module is the reading at the heart of a week’s work, and the order of the four pieces matters:
- Read the module, start to finish. The prose matters as much as the code — each concept is explained in words before it appears in R, and the code clicks more quickly once you’ve worked through the reasoning first.
- Do the pre-study (Friday, 10:00–11:00 am — or any time before Monday’s lecture). Its short videos and hands-on activities build directly on what you just read and add no new material, so the module always comes first. Finish both the module and the pre-study before lecture.
- Come to Monday’s lecture (10:00–11:30 am, in person) having read the module and worked through the pre-study. Lecture applies the material to harder problems and connects it to your own research — arriving prepared means you can engage with the ideas rather than play catch-up.
- Practice in Wednesday’s lab (3:30–4:45 pm, in person). Hands-on coding with the instructor in the room — this is where the week’s material becomes something you can actually do.
- Render and submit your lab by 11:59 pm Tuesday — midnight before the next lab meets. That gives you the lab session plus six days, and it is the one deadline in the weekly cycle.
The modules are the foundation that makes lecture and lab productive — not a substitute for them.
Why the order matters. Part of the course grade is Engagement, and what it rewards is this sequence: arriving on Monday having read the module and worked the pre-study, and arriving Wednesday ready to write code. It is not a measure of how much you talk. The syllabus sets out the scale and what we look for.