3.1 Assignments
Your grade for this course will consist of a number of different assignments on which points may be earned. Each category of assignment is described below.
3.1.1 Attendance and Participation
Attendance and participation are worth 10% of your final grade.
Both attendance and participation are critically important aspects of this class. The class participation grade will be based on (a) attendance, (b) level of engagement during lectures and labs, (c) level of engagement on Slack, and (d) the completion of other exercises including “entry” and “exit” tickets, the student information sheet, a pre-test, and an end of the semester course evaluation.
Each of these elements is assigned a point value and assessed using a scale that awards full, partial, or no credit. Your participation grade will be split, with 50 points (5% of your final grade) for the first half of the semester (through Lecture-08) and another 50 points (5%) for the second half. Since the number of points awarded for participation are variable, the total number of points earned for each half will be converted to a 0 to 50 scale.
I provide the final number of points earned for each half of the course. If you would like a more detailed breakdown of your participation grade, please reach out and I will provide one.
3.1.2 Lecture Preps
Lecture preps are worth 6% of your final grade.
Before each course meeting, you will need to complete all assigned readings. For a part of these readings, you will also need to complete a short exercise. These prep exercises are designed to get you ready for the week’s material by exposing you to basic, guided examples before class begins. Instructions for the lecture preps will be posted in the lecture repositories on GitHub and will be linked to from the lecture pages on the course website. The instructions will also detail the deliverables to be submitted to demonstrate completion of each assignment.
For many of the lecture preps, I will post a YouTube video of me completing the exercise and narrating the process. These videos will be embedded in the lecture pages on the course website. You should follow along with the video and use it as a guide for completing the exercise yourself. I will also post replication files that detail the process and, if relevant, the code for completing the lecture prep. Like the instructions, these will be posted in the lecture repositories on GitHub.
There will be a total of fifteen lecture preps over the course of the semester, each of which is worth 4 points (0.4% of your final grade). Lecture preps are graded using the “check” grading system. Since replication files are posted, feedback for lecture preps is not generally returned and I will only respond with the number of points awarded if you do not earn full credit.
3.1.3 Lab Exercises
Labs are worth 15% of your final grade.
Each course meeting (except the first) will include time dedicated to practicing the techniques and applying the theories described during the day’s lecture. These exercises will give you an opportunity to practice skills that correspond with the first four course objectives. Instructions for the labs will be posted in the lecture repositories on GitHub and will be linked to from the lecture pages on the course website. The instructions will also detail the deliverables to be submitted to demonstrate completion of each assignment. Replication files are also provided in the lecture repositories on GitHub.
Lab exercises will be completed in small workgroups, though each student is expected to turn in the required deliverables. We will assign students to workgroups and may shuffle their composition over the course of the semester. Completing a lab entails not just successfully submitting the required deliverables but also actively contributing to the group discussions that help to produce them.
There will be a total of fifteen lab exercises over the course of the semester, each of which is worth 10 points (1.5% of your final grade). Lab exercises are graded using the “check” grading system. Since replication files are posted, feedback for labs is not generally returned and I will only respond with the number of points awarded if you do not earn full credit.
3.1.4 Problem Sets
Problem sets are worth 28% of your final grade.
Problem sets will require students to draw on a variety of skills, including cleaning data, performing statistical analyses, producing plots, and reporting results. They are designed to assess your progress with the first four course objectives. Instructions for the problem sets will be posted in the lecture repositories on GitHub and will be linked to from the lecture pages on the course website. The instructions will also detail the deliverables to be submitted to demonstrate completion of each assignment. Replication files that illustrate my approach to each problem set will be posted on GitHub in the Replications repository once all students have submitted their problem sets.
There will be a total of eight problem sets over the course of the semester, each of which is worth 35 points (3.5% of your final grade). Each Problem Set will include a simple rubric describing how each problem set is evaluated. A key aspect of these assignments is not only demonstrating comfort with a particular set of statistics skills, but also demonstrating and evolving in your analysis development, programming, and analytical skills as well. The weight given to quality of your process and code will increase as the semester progresses.
3.1.5 Final Project
The final project is worth, in total, 41% of your final grade. Depending on your section, it will be broken down into a variety of assignments, each of which has their own point value. See below for details.
The final project corresponds with the fourth learning outcome. It will be organized slightly differently depending on which section you are enrolled in. Specific instructions will be provided in the final project guide, and updates will be posted on the course website’s final project page.
In brief, all students will select a topic and submit their topic by Lecture-03 (September 10th) as an “Issue” in their individual GitHub assignments repository. Groups will be formed based on topic area. These groups will be used for support throughout the semester as well as peer review of particular pieces of the project itself.
As work progresses, there will be a number of waypoints where students will need to submit updates on their progress. Waypoints beyond the memo submission are as follows:
- Lecture-05 (September 24th) - Progress report from each student due as a GitHub issue in each student’s final project repository
- Lecture-08 (October 15th) - Progress report from each student due as a GitHub issue in each student’s final project repository
- Lecture-11 (November 5th) - Draft materials due in each student’s final project repository
- Lecture-12 (November 12th) - Peer reviews due to group members as a GitHub issue in each student’s final project repository
- Lecture-15 (December 3rd) - Progress report from each student due as a GitHub issue in each student’s final project repository
- Final Presentations (December 17th) - Response to reviewer due in the GitHub issue opened by the reviewer
Deliverables for each waypoint are described in the final project guide. All waypoints are graded using the “check” grading system. Final materials will be due on December 17th (during Finals Week), when we will hold a “research conference” in Morrissey Hall. During our conference, each student will present their results using PowerPoint (or similar). Final deliverables differ by course section.
3.1.5.1 SOC 4015
If you are enrolled in SOC 4015, you will need to pick a continuous variable from the 2012 General Social Survey to use as your main study variable. You will then clean the data and conduct an analysis of this variable using a variety of statistical tests covered this semester. Your final results will be presented as a PowerPoint presentation during finals week.
| Assignment | Points | Quantity | Total |
|---|---|---|---|
| Memo | 20 pts | x1 | 20 pts |
| Waypoints | 20 pts | x6 | 120 pts |
| Draft Code & Docs | 20 pts | x1 | 20 pts |
| Draft Slides | 20 pts | x1 | 20 pts |
| Final Code & Docs | 100 pts | x1 | 100 pts |
| Final Slides | 100 pts | x1 | 100 pts |
| Final Presentation | 30 pts | x1 | 30 pts |
3.1.5.2 SOC 5050
If you are enrolled in SOC 5050, you will need to identify an appropriate data set that contains a continuous variable that you can use as your main study variable. You will then clean the data and conduct an analysis of this variable using a variety of statistical tests covered this semester. Your final results will be presented as a PowerPoint presentation during finals week.
You will also have to produce a 5,000 word final journal article manuscript that places your project in the relevant social science literature, presents your data and methods, and provides a summary and discussion of your results. An annotated bibliography will be due at Lecture-07 (October 8th) and the draft paper will be due at Lecture-12 (Novemeber 12th; note that this is one week after the other draft materials). Peer reviews of papers will be due at Lecture-13 (Novemeber 19th).
| Assignment | Points | Quantity | Total |
|---|---|---|---|
| Memo | 10 pts | x1 | 10 pts |
| Waypoints | 10 pts | x7 | 70 pts |
| Annotated Bibliography | 15 pts | x1 | 15 pts |
| Draft Code & Docs | 15 pts | x1 | 15 pts |
| Draft Slides | 15 pts | x1 | 15 pts |
| Draft Paper | 15 pts | x1 | 15 pts |
| Final Code & Docs | 35 pts | x1 | 35 pts |
| Final Slides | 100 pts | x1 | 100 pts |
| Final Presentation | 35 pts | x1 | 35 pts |
| Final Paper | 100 pts | x1 | 100 pts |