Assignments

“Tracks” for this course

Especially in the first half of the course, there will be two “tracks” - one called Application (APP) and one called Computational/Statistical Development (CSD) - with different homework assigned to each group, and some assigned to both. Your backgrounds are heterogeneous, and this will help grow your skills based on your background.

• The APP track is intended for SDS Majors (or intended majors) who plan for this course to fulfill the SDS Application Domain. The assignments will be more conceptual, reading intensive; the goal will be to develop an understanding of population health content that will round out your statistical background.
• The CSD track is intended for non-SDS-majors and is oriented on developing expertise in R, regression modeling, and other statistical domains that will be needed for the group project (and in the field of population health).

In the second half of the course, these paths should converge such that everyone has a similar skill set in the content and methods of population health analyses.

Homework

Homework is defined broadly for this course and included a variety of activities, particularly reading, problem sets, and online modules. Specific assignments and deadlines are included on the schedule, including by “track” (see above); more detailed information about assignments will be here as needed.

Reading Response Papers

The goal of response papers are to offer a space and structure for your thoughts about the readings. In some cases, these responses will be on additional readings that go into further depth after a topic has been introduced. These papers may also be in advance of course meetings, where you may be thinking about a topic for the very first time. In either situation, the goal is not simply to summarize the reading (I’ve read these papers already!) or merely to prove that you did the reading. To be fair, you may need to summarize the main findings or argument of the paper, but that should be done succinctly and only as a means to the end of getting your perspective on the paper. I want you to show me how you’re thinking about a given topic, what you’re grappling with, what is clear and what remains unclear. There is no clear write or wrong answer; no one can write an incorrect response paper, per se, so long as you are genuinely using it as an opportunity to reflect your thoughts on the reading.

To make this a little more concrete, here are some questions you might pose as you’re reading or to prompt your own thinking about the material:

• If these are readings done after class, how, if at all, do these ideas connect with what was covered in class? What do you
• What did you find exciting about the paper? What, if anything, was new and invigorating?
• What do I agree with? And more importantly, what did I disagree with? Why? Where were the authors particularly/insufficiently compelling?
• What did you think was good about the paper? What was done well, either in the style (e.g., well written), content, or methods.
• What was missing from the paper?
• What didn’t you understand? Where could the authors have been clearer?
• How does this connect to other work you’ve done, either in this class or other classes, or to relevant personal/professional experiences. Does it change what you are thinking about for your course project?
• For older papers, what do you think has changed since this paper?
• For theoretical papers, are these ideas testable? What would you need to test them?
• For empirical papers, what theories, conceptual framework, or ideas seemed to inform the analysis? Were the authors explicit about how their perspective informed their decision-making?

These are not all to be covered in a given response paper; instead, they’re prompts that are meant to get you thinking about your reading.

The tone can be casual and informal. These are meant to be written more like a journal entry or personal blog post than they are research papers.

The papers should be approximately 1 page double-spaced or 1/2 page single spaced; they can be a little shorter or go a little longer, but should be between 1/2-2 pages double spaced (or single spaced equivalent) . They can be submitted as either a Word or PDF document.

DataCamp Modules

There will be a few modules from DataCamp, “the first and foremost leader in Data Science Education, offering skill-based training, pioneering technical innovation, and courses from the world’s best educators,” to introduce R to new users and refresh/expand previous statistical coursework in regression modeling from those who have not taken SDS 291 or an equivalent (e.g., Econometrics) that will be used in the course project.