A.4 Practical matters

A.4.1 Expectations

Class ground rules: This course operates in a safe, respectful, and inclusive environment. That applies to class meetings, office hours, posting on discussion boards, and any other communications you send as part of this course. As a college and a community, we value diversity of age, race, ethnicity, gender identity and expression, sexual orientation, religious affiliation, disability, and other identities, visible or nonvisible.

If at any time during this course you are made to feel uncomfortable or unwelcome, I encourage you to talk to me about it. You can also use one of the other contact methods described in the resources.

Academic integrity and the honor code: You’re responsible for doing your work in this course both in accordance with stated rules (which may be different for different assignments) and with a sense of fairness and integrity. The section of the student handbook dealing with the Honor Code can be found here: https://www.mtholyoke.edu/student-handbook/student-accountability.

Very briefly, academic integrity means that you do not seek any unfair advantages over other students, and that all work you present as your own is your own. But the details of that can get complicated. I’ve tried to be very clear about what collaboration and resources are appropriate for each assignment, but if you have any questions or uncertainties about what something means, or whether something is okay, please contact me. I am very happy to talk to you about this. I am much, much happier to talk to you about it before something happens.

One issue that people tend to struggle with in this course is plagiarism. Yes, it is possible to commit plagiarism in stats or math! Sure, there are fixed vocab words and equations that everyone uses, but your explanations and discussions should always be your own creation. Any time you take someone else’s words/ideas without citing them is plagiarism – even if it’s just my notes, or the built-in R documentation, or even an AI. Again, I’m happy to talk with you about this. You can also find a helpful guide to avoiding plagiarism here: https://plagiarism.arts.cornell.edu/tutorial/index.cfm.

On a related note: a few words about AI tools, ChatGPT, etc. You may not use any such tools to generate work you present as your own. No, not even if you edit the text it gives you. Not even for translation purposes. Not even if the assignment isn’t graded. If you use any AI tool to generate anything, you must quote it and cite it as if it were a person or a book you were using; anything else is plagiarism, and yes, I will report it to the Academic Honor Board.

Why am I such a stickler about this? Two reasons:

  1. You’re here to learn things. This course isn’t just here to fill up a blank space on your transcript; it’s here to help you develop skills – both statistical skills and communication skills. If you use AI, or other non-permitted resources, you don’t develop those skills in the same way or to the same extent. You’re paying good money for this course (or somebody is); don’t cheat yourself out of the benefits.

  2. AI is not actually good at this. Current AI tools like ChatGPT are language models: they create plausible English sentences. They are not designed to create true sentences. They don’t even try to! They have no concept of truth (except where developers have implemented guardrails, and they’re not really prioritizing guardrails for the kinds of things we talk about in this course!). Tools like this will give you lengthy paragraphs filled with smooth, syntactically correct sentences half of which are wrong, or irrelevant to the context. Trying to figure out which parts are correct or relevant takes so much work that you should’ve just written your own answer in the first place.

Prerequisites: Stat 242 or equivalent, Math 211 (linear algebra) or equivalent, and a willingness to devote regular time to working on this course. Stat 340 is highly recommended (at least taking it concurrently); we’ll be working with multivariate models and regression in this course, and we’ll be going through it pretty fast. I assume that you have worked with R before.

In general, if you are ever unsure whether you’re supposed to know some bit of material already – or concerned that you don’t – I encourage you to ask me (or a classmate!) about it. Sometimes I actually don’t expect you to know it yet. And if I do expect you to know it, I’m happy to get you the help you need to pick it up.

A.4.2 Access and accommodations

Accessibility: My goal is to create a class that’s accessible, inclusive, and rewarding for everyone. This means accommodating everyone’s disability and accessibility needs, in addition to any logistical issues that may come up.

If anything like this applies to you, come and talk to me. Sooner is better! You can also get in touch with the folks over at Disability Services (https://www.mtholyoke.edu/directory/departments-offices-centers/disability-services) for much more help.

Exceptions, extensions, etc.: This course is designed so that the flexibility and exceptions are already built in! (See more here.) But if something major comes up that stretches that built-in flexibility, tell me about it as soon as possible. We may be able work out an alternative plan or accommodation, but there is much less I can do if you come to me after the fact. See here for more on this.

A.4.3 Materials

Books: There is one required textbook for this course: Forecasting: Principles and Practice by Hyndman and Athanasopoulos, 3rd edition. It’s available online for free at https://otexts.com/fpp3/. You can also order a downloadable version or a hard copy (not free) if you want to.

We may also draw on some other resources, but it won’t be anything you have to pay for :)

Electronics: You will also need a suitable electronic device. All of the work for this course should be doable via web browser; we’ll be using RStudio Server so you do not need to install R on your local device, although you can if you want to. (Note that you will need to be on an MHC network or connected to the VPN to access RStudio Server! Ask me or LITS if you have questions about this.)

Although you won’t need R installed on your own machine, you will need to do a lot of typing and have multiple things open at once. I recommend you have access to an actual computer unless you’re really good with a teeny tiny keyboard, though you can certainly use your phone/tablet for some things during the course. If you have any questions or issues around devices (including accessibility issues, restrictions on screen time, not having a laptop to bring to class, etc.) let me know.