Editing Statistics and Statistical Programming (Fall 2020) (section)

=== Format and structure ===
<!---
I expect everybody to come to class, every week, with a laptop and a power cord, ready to answer any question on the problem set and having uploaded code related the the programming questions. The class is listed as nearly 3 hours long and, with the exception of short breaks, I intend to use the entire period. Please be in class on time, plugged in, and ready to go.
--->

This course will proceed in a '''remote''' format that includes ''asynchronous'' and ''synchronous'' elements (more on those below). In general, the organization of the course adopts a "flipped" approach where participants consume, discuss, and process instructional materials outside of "class" and we use synchronous meetings to answer questions, address challenges or concerns, work through solutions, and hold semi-structured discussions. 

The course introduces ''both'' basic statistical concepts as well as applications of those concepts through statistical programming. As a result, we will usually dedicate part of each week to a particular set of concepts and part of each week to applied data analysis and/or interpretation. A brief description of how I expect it all to work follows below. We'll talk about it more during the first class session.

====Asynchronous elements of the course====

These include all readings, recorded lectures/slides, tutorials, textbook exercises, problem sets, and other assignments. I expect you to complete (or at least attempt to complete!) these outside of our class meeting times. I also strongly encourage you to identify, submit, and discuss questions about the material '''before each class meeting''' whenever possible.

We will use Discord for everyday discussions and chat related to the course. In general, the teaching team will try to keep an eye on the various server channels during "business hours." To the extent that we can respond to questions and concerns there, we'll do so. We'll also use the discussion channels to identify topics that might benefit from synchronous conversation during the course meetings. Hopefully, writing and talking about questions and concerns outside of the synchronous course meetings will help support accountability, learning, and more effective use of our meeting time.

For nearly all of the "instructional" material introducing particular statistical concepts and techniques, you are assigned materials from the OpenIntro textbook and lecture materials created by the textbook authors. Please note that this means I will not deliver lectures during our class meetings. Please also note that this means you are responsible for coordinating your working groups and any collaborative work with other members of the class outside of our class meeting times.

====Synchronous elements of the course====

The synchronous elements of the course will be the two weekly class meetings that will happen via video conference (Zoom). These are scheduled to run for a maximum of 110 minutes. Each session will include multiple short breaks. 

We will use the class meetings to discuss and work through any questions or challenges you encounter in the materials assigned for that day. This means that I encourage you to identify, submit, and discuss questions about the material '''before each class meeting''' whenever possible. Doing so will give the teaching team time to sift, sort, and organize the questions into a hopefully-cohesive plan for each class session that is tailored to the specific concerns you encounter in the material. Obviously, we anticipate that questions will arise during the class sessions too as well and we'll do our best to adapt as we go.

A couple of other notes about the synchronous course meetings:
* Aaron plans to record the course meetings and have them available to class participants only via Zoom/Canvas. Please get in touch if you have concerns or requests about this. 
* The teaching team will do our best to notice and respond to any questions or comments that come up via Discord or Zoom during the class. Please do what you can to support these efforts.
* You might want to create/acquire something like [https://www.mccormick.northwestern.edu/news/articles/2020/08/back-to-school-hack-shares-students-handwritten-work-and-teacher-response-in-real-time.html NU Mechanical Engineering Professor Michael Peshkin's homebrew document camera] to facilitate sharing hand-written notes/drawings during class.

In addition, because randomness is extremely important in statistics, I may occasionally '''randomly assign''' different working groups to share and discuss their solutions to selected textbook exercises or problem set questions during class. These random assignments will be announced ahead of time so that the group has an opportunity to prepare. The idea here is to structure some participation in the synchronous sessions to ensure an equitable distribution of the responsibility to discuss questions, answers, points of confusion, and alternatives.

==== Working groups ==== 

At the start of the course you will be assigned to a small working group. This will be a group of 2-3 students (exact numbers will depend on the final enrollment) with whom you may meet outside of class time to discuss, complete, and/or review your weekly assignments (as well as some of the research project assignments). The groups will rotate at least once during the quarter to ensure that you get to work with different members of the class. The main idea is to support collaborative learning, peer support, and accountability. While the specifics of exactly when and how you work with your working group will largely be up to you, the teaching team will provide [[Statistics_and_Statistical_Programming_(Fall_2020)/Working_groups_template|suggestions in the form of a template]] that you can use as a starting point.

As a general rule, we strongly encourage you to collaborate with members of your working group on any/all weekly (minor) assignments. You may, if you choose, also collaborate with others in your group or the class on your research project (major) assignments; however, collaborative research projects should be discussed with a member of the teaching team and all research project assignment submissions should include the names of all collaborators. 

<!---
Although the day-to-day routine will vary, each class session will generally include the following:
* Quick updates about assignments, projects, and meta-discussion about the class.
* Discussion of '''programming challenges''' due that day (and related to the previous week's R lecture materials).
* Discussion of  '''statistics questions''' related to new material in Diez, Barr, and Çetinkaya-Rundel.
* Discussion of any exemplary empirical paper we have read and the '''empirical paper questions'''.
--->