Syllabus

SUPER DRAFT

Course objectives

By the end of this course, you will (1) be data literate and (2) be able to answer your own questions with statistical and data scientific tools.

Specifically, you’ll be able to:

Be curious and confident with data
Feel comfortable with R
Tidy and wrangle data imperturbably
Find patterns in data with appropriate graphs and visualizations
Pose and test insightful hypotheses
Accurately interpret results from basic inferential statistical analyses
Understand the assumptions and limitations of statistical procedures
Communicate the results of your analyses in accessible language

Course philosophy

Classical statistics classes spend substantial time covering probability theory, null hypothesis testing, and other statistical tests first developed hundreds of years ago. Some classes don’t use software or actual real data and instead live in the world of mathematical proofs. They can be math-heavy and full of often unintuitive concepts and equations.

In this class, we will take the opposite approach. We begin with data and learn how to tidy, wrangle, manipulate, and visualize it with code. Later in the semester we turn to more classical topics like inference and statistical modeling, but continue to keep the focus on data as we do so.

In other words, there’s way less of this:

\[ f(x) = \dfrac{1}{\sqrt{2\pi}} e^{-\frac12 x^2} \]

And way more of this:

gdp_by_region <- gdp_data |>
  group_by(region) |>
  summarize(
    avg_gdp = mean(gdp), 
    sd_gdp = sd(gdp)
  )

Over the last decade there has been a revolution in statistical and scientific computing. Open source languages like R and Python have overtaken older (and expensive!) corporate software packages like SAS and SPSS, and there are now thousands of books and blog posts and other online resources with excellent tutorials about how to analyze pretty much any kind of data.

This class will expose you to R—one of the most popular, sought-after, and in-demand statistical programming languages. Armed with the foundation of R skills you’ll learn in this class, you’ll know enough to be able to find how to analyze any sort of data-based research question in the future.

Course policies

Generative AI and LLMs

In this class, I have two general rules regarding LLMs:

Everything human-facing must be human-generated.
You are responsible for understanding, verifying, and citing everything an LLM generates.

I’ll explain what these mean below, but first, an important warning!

LLMs and learning

Phew, I can talk about the relationship between learning and LLMs for hours (see this for a more formal explanation of my thinking). LLMs and generative AI can be useful for statistical programming, but only when you already know what you are doing. They can be dangerous and counterproductive for beginners.

Additionally, using LLMs and generative AI to write does not lead to deeper learning. The point of writing is to help crystalize and organize your thinking. Pasting LLM-generated words into an assignment to make it look like you read and understood the content will not help you learn. Pasting LLM-generated code into an assignment and hoping that it works will not help you learn.

Rule 1: Everything human-facing must be human-generated

Generative AI tools like Gemini, ChatGPT, and Claude can be helpful for generating ideas or topics for your assignments and can even help you find existing research about topics you’re interested in. They are useful for debugging and troubleshooting code.

These uses are permitted in this course.

If you want to use LLM tools to document your code, clean up your notes, look up error messages, search for research related to your topic, and so on, cool. Do it. That’s fine. It’s unavoidable nowadays anyway, since every R-related Google search will give you a Gemini-generated answer at the top with mostly working R code.

Any writing and revisions, however, must be your own. You may not use AI tools to write any of the text you submit to me. AI text adds nothing to my understanding. I have no interest in engaging with it at all. There is nothing more disheartening for me than spending my time grading something that ChatGPT spat out in 10 seconds. I want to see good engagement with the readings. I want to see your thinking process. I want to see you make connections between the readings. I want to see your personal insights. I don’t want to see a bunch of words that look like a human wrote them. That’s not useful for future-you. That’s not useful for me. That’s a waste of time.

Thus, anything human-facing (i.e. not stuff done just for yourself, like your own personal notes, research, etc.) must be human-generated (i.e. written by you). You may not use AI tools to write any portion of your assignments. Using AI tools in this way, or failing to disclose the use of AI tools, will be treated as a case of plagiarism and referred to the Honor Council.

Rule 2: You are responsible for understanding, verifying, and citing everything an LLM generates

These tools are really good at working with code, but again, only if you know what you’re doing. Without guidance and expertise, LLMs love making lots of extraneous, convoluted, and weird code by default. The code ostensibly works, but it’s often strange and unnecessary and uses uncommon syntax and packages.

If you use LLMs for help with code, you must understand and verify what’s going on with your code and you must cite where it came from.

This means that you need to know what each line is doing. If the LLM uses a function or gives you an argument that you don’t understand or haven’t seen before, figure out why and figure out if it’s necessary. Look at the documentation for the function. Search Google for other examples. Ask the LLM about it, and then add comments to the code explaining what’s going on.

The citation doesn’t need to be anything formal (i.e. don’t worry about Chicago or APA guidelines)—it just needs to (1) say which LLM you used, and (2) mention what you asked the LLM.

You should do this by using code comments—inside your code chunk, add a # to the beginning of a line so that it’s treated as a comment (or text) instead of actual code.

Here’s an example of what this can look like:

# This calculates the average GDP per capita in each region in the dataset, 
# for all countries after 2015. I couldn't remember how to use group_by() and 
# summarise() together, so I asked Gemini:
# 
# "I'm using tidyverse. I have a dataset named my_dataset and I'm filtering it 
# to include all countries after 2015. I want to calculate region averages with 
# group_by and summarise but cannot remember the syntax"

my_dataset |> 
  filter(year > 2015) |> 
  group_by(region) |> 
  # Gemini here included na.rm = TRUE, which omits any rows with missing values 
  # when calculating the average. That's okay and necessary here because 
  # South Sudan is missing some years of GDP data
  summarise(avg_gdp = mean(gdp_per_cap, na.rm = TRUE))

# Gemini also included an extra ungroup() function at the end, but I don't need 
# that because there are no groups leftover after summarising here

↑ That’s a lot of extra comments and you won’t always see stuff like that in real life code, but I want to see it here, and future-you will want to see it too.

Participation

Given the interactive style of this class, participation will be crucial to learning and your success in the course. Attendance is particularly important also because in-class assignments and discussion will be a critical component for your learning and grade. As such, each in-class assignment will be graded for both content accuracy and contribution, and that will take the place of a traditional participation grade.

Attendance and absences

Your presence in class is crucially important. That said, I understand that life can bring surprises, so your first three absences (for whatever reason) will not affect your grade. After three absences, every additional absence (no matter the reason for the absence) will reduce your overall participation grade by one full letter grade.

Collaboration

Collaboration is crucial to the learning process and our course’s objectives. In-class assignments and larger assignments on Canvas will specify whether the work should be done collaboratively, in pairs, or individually. Please be intentional: if a submission should be done individually, submit only that which is exclusively your work (with appropriate citations, of course). For collaborative assignments, you will be randomly placed in groups unless otherwise specified; please remember to include the full name of each group member on assignments.

Deadlines and late work

Students should make every effort to submit their assignments and materials on time in order to ensure prompt feedback and grading. However, we are all human and things happen. In the event that a deadline is missed or going to be missed, please reach out so we can discuss make-up assignments and set new timelines. If you feel at any point that you are overwhelmed with deadlines or are falling behind, please reach out as soon as possible.

Communication

Like you, I have a full life beyond this course, and so may not always be able to respond to emails immediately. In general, I am only on my GU email account on weekdays from 9am–5pm. Not counting weekends, I will endeavor to respond to you within 48 hours. Please note that emailing me right before an exam or major assignment may not guarantee feedback or a response in time to impact your work, so please plan your time accordingly.

Technology use

Technology (laptops, tablets, phones) may be used in class only at specific times and for specific activities set by the instructor. Outside of those moments, please keep devices stowed so we can give the discussion our full attention. If you have accommodation needs around technology registered with the Academic Resource Center, let me know.

Class recording

To protect the privacy of your peers and maintain an environment of open intellectual exchange, students are not permitted to record (audio or video) any part of our class sessions. This includes the use of transcription software or AI assistants. Exception for approved accommodations: students with a disability-related recording accommodation approved by the Academic Resource Center (ARC) are permitted to record solely for their personal study. Unauthorized recording or dissemination of class content is a violation of University Policy and may be referred for disciplinary review.

Instructional continuity

If meeting in person is impossible for a given session (e.g., if the campus is closed), we will meet virtually at the Zoom link posted on Canvas.

Office Student hours

Student hours are set times dedicated to all of you (most professors call these “office hours”; I don’t¹). This means that I will be waiting for you to talk to me (in person or remotely) with whatever questions you have. This is the best and easiest way to find me and the best chance for discussing class material and concerns.

The best way to meet with me is to make an appointment with me here. You can choose an online or in-person slot—if you choose an online slot, the confirmation e-mail will contain a link for a Zoom meeting. You can also find me through e-mail and Discord.

University policies and resources

Academic integrity and the honor code

Students at Georgetown University are expected to maintain the highest standards of academic and personal integrity. Academic dishonesty in any form is a serious offense, and students found in violation are subject to academic penalties that include, but are not limited to, failure of the course, termination from the program, and revocation of degrees already conferred. All students are expected to fully adhere to the policies and procedures of Georgetown’s Honor System and to take the Honor Code Pledge:

In pursuit of the high ideals and rigorous standards of academic life I commit myself to respect and to uphold the Georgetown University honor system: to be honest in every academic endeavor, and to conduct myself honorably, as a responsible member of the Georgetown community as we live and work together.

All submissions must be your original work. The Georgetown University Honor System defines plagiarism as “the act of passing off as one’s own the ideas or writings of another.” Any submission suspected of plagiarism will be referred to the Honor Council for investigation and possible adjudication. Note the Honor Council’s Standards of Conduct on AI-generated work: if you didn’t generate the words yourself, say so by quoting and citing the source; if you generated the words but not the content and ideas, say so by citing the source. Whether AI-generated work is allowed at all is governed by the course policy above.

Students with disabilities and accommodations

Under the Americans with Disabilities Act (ADA) and the Rehabilitation Act of 1973, individuals with disabilities have the right to specific accommodations that do not fundamentally alter the nature of the course. Students are responsible for communicating their needs to the Academic Resource Center (202-687-8354; arc@georgetown.edu), the office that oversees disability support services, before the start of classes to allow time to review the documentation and make recommendations for appropriate accommodations. The University is not responsible for making special accommodations for students who have not declared their disabilities and have not requested an accommodation in a timely manner. For the most current policy information, please refer to the Georgetown University Academic Resource Center website.

Accessibility and inclusion

One of the central tenets of Georgetown’s educational mission is cura personalis, a Latin phrase meaning “care of the whole person.” I am committed to creating a learning environment that supports a diversity of thoughts, perspectives, and experiences, and honors your identities. If your name or pronoun needs to be corrected, please let me know early in the semester so that I can make the appropriate changes to my records.

Title IX and sexual misconduct

Georgetown University and its faculty are committed to supporting survivors and those impacted by sexual misconduct, which includes sexual assault, sexual harassment, relationship violence, and stalking. Georgetown requires faculty members, unless otherwise designated as confidential, to report all disclosures of sexual misconduct to the University Title IX Coordinator or a Deputy Title IX Coordinator. If you disclose an incident of sexual misconduct to a professor in or outside of the classroom (with the exception of disclosures in papers), that faculty member must report the incident to the Title IX Coordinator or Deputy Title IX Coordinator, who will in turn reach out to the student to provide support, resources, and the option to meet. The student is not required to meet with the Title IX coordinator. If you would prefer to speak to someone confidentially, Georgetown has fully confidential professional resources, including Health Education Services for Sexual Assault Response and Prevention (confidential email: sarp@georgetown.edu) and Counseling and Psychiatric Services (CAPS: 202-687-6985). More information about reporting options and resources can be found on the Sexual Misconduct Resource Center website. Georgetown is also committed to creating an accessible and inclusive environment for pregnant and parenting students; students seeking a pregnancy adjustment or accommodation should follow the process laid out on the Title IX at Georgetown website.

Support services

Resources available to you include: Academic Resource Center (202-687-8354, arc@georgetown.edu); Counseling and Psychiatric Services (202-687-6985); Institutional Diversity, Equity & Affirmative Action (202-687-4798); the Georgetown Library and its eResources (500+ research databases, 1.5+ million ebooks); the Writing Center (peer tutoring at any stage of the writing process); and the Office of the Student Ombuds (studentombuds@georgetown.edu, 202-784-1081)—a confidential, independent, impartial, and informal space to discuss University-related concerns. All students have 24/7 access to Canvas technical support via the Help icon in Canvas or the support hotline at 855-338-2770.

Footnotes

There’s fairly widespread misunderstanding about what office hours actually are! Many students often think that they are the times I shouldn’t be disturbed, which is the exact opposite of what they’re for!↩︎