Here is the R code we will review in the bootcamp Download
Answers: Download
Slides (html) Open
Slides (pdf) Download
R code (we won’t be going over code) Download
Answers: Download
In these notes, you can get a refresher from the material covered in STA 301:
I will be uploading short videos in this section, mainly focused on R coding, but also other topics, depending on what is needed!
Go to VideosSome Useful R Code: I put together this short document showing some useful packages and functions that might come in handy during this course!
For those that want some R refresher, these external resources can be useful:
Introduction to R programming by Jacob Jameson. It’s a beginner-friendly start-up guide, that includes short videos and labs to test your skills. If you’re very lost in R, this might be a good place to start.
Introduction to Data Science by R. Irizarri (2021). Check out specifically R Basics, the tidyverse, and ggplot.
YouTube Playlist by Prof. James Scott, used in STA 301.
An introduction to R (with a focus on the tidyverse) by Jenny Bryan.
A ModernDive into R and the tidyverse (by Ismai and Kim).
R for the Rest of Us. (by David Keyes)
Cheatsheets for R are amazing! Here are two of my favorite so you can look up functions we will be using frequently explained in a simple way:
Check out the starting tutorial here (see all the references in this document!)
Introduction to the Potential Outcomes Framework by G. Basse & I. Bojinov (2021), from their blog Causal Conversations.
What is causal inference? by G. Basse & I. Bojinov (2021), from their blog Causal Conversations.
A Leader’s Guide to Interference (also known as spillover effects) by G. Basse & I. Bojinov (2021), from their blog Causal Conversations.
Correlation and Causation by G. Basse & I. Bojinov (2021), from their blog Causal Conversations.
Brady Neal - Causal Inference. (2020). “Ignorability/Echangeability”.
1) Is there a specific format I should follow when emailing a professor?
This is an important question, and not only for professors! (Disclaimer: This is part of a much larger hidden curriculum, so don’t worry if you don’t get it right straight away).
Useful tips for emailing a professor (or really anyone in a professional setting):
Use an informative subject: In this case, “[STA 235H] Your subject” is a good idea so I can immediately identify emails from students.
Always include an appropriate greeting!: Most students have this down, but “Hey” is usually not considered professional (or no greeting at all, when you are starting an email chain). When addressing professors, usually a good greeting would be “Dear Prof. Smith” or even “Hi Dr. Smith” (both work fine!). Try to avoid “Mr.” or “Ms.” (and stay far, far away from “Miss” or “Mrs.”) when referring to a professor.
Quickly introduce yourself: Reminding professors who you are is always a good idea (especially in the first email you ever send). We are usually handling multiple sections and hundreds of students, so it’s a good way to help us remember names. Something like “I’m in your Tuesday 10am class” works great, because I can pin down the section.
Be clear about the motive of the email: Feel free to use bold fonts, underscore, etc. and try to keep emails succinct. That way you are sure that your point is coming across and is more likely that you get the appropriate response.
2) Should I go to office hours?
The answer is almost always YES!. Office hours are a great way to just check your knowledge or ask any question you might have in a non-judgement zone. Even if you don’t know what to ask but feel somewhat lost, we can work backwards and try to pinpoint some of the key elements that might be confusing and start from there.
3) What do I do if I get stuck with some code?
An important part of this course is for you to learn how to “teach” yourself how to code. How’s that? New tools (and languages!) are coming up more rapidly than you’ll be able to see in one class, so it’s an important asset for you to learn how to find some answers by yourself. If you Google an error that you got in R, most likely you’ll be able to find the answer on very useful websites like Stackoverflow (believe me, I (and everyone who codes) do it all the time).
However, I don’t want you to get stuck either! If you don’t find the answer quickly on the internet (say, 10 min.), please reach out to the instruction team on Canvas. We are here to help!
4) Notation is too hard! Can we get a cheat-sheet for this?
Ask and you shall receive! I created this short cheat sheet which hopefully helps. Let me know if you want me to include something else!