Policies
Evaluation:
Your final grade will be comprised of the following:
| Item | % |
|---|---|
| Preparation and participation | 15% |
| Programming assignments | 40% |
| Online presentation | 10% |
| Midterm exam | 15% |
| Research project | 20% |
| - paper (8%) | |
| - presentation (6%) | |
| - peer review (6%) |
Preparation and participation
Students are expected to attend class prepared and to actively participate.
Part of this grade is derived from reading summaries. Students will occasionally be required to write a brief summary (max. 1 page) of the weekly readings and answer assigned questions. Summaries, when assigned, will be handed in via sakai dropbox the day before class meets, before 10pm.
Programming assignments
Students will complete 4 programming assignments over the course of the semester. These assignments are designed in a way so that the student must demonstrate adequate knowledge of basic programming principles covered in class. The skills required in each assignment are cumulative, each building on the material learned in the previous weeks. All statistical programming assignments must be completed in RMarkdown and will be handed in via GitHub.
Online presentation
The presentation will be on the statistical analyses used in some published paper. This presentation must be hosted on GitHub and in HTML format using RMarkdown. Aside from creating an online presentation, students will also be required to read and comment on the presentations of two classmates. More information available here
Midterm exam
There will be an in-class exam during the 11th week of the semester (April 3rd). Details will be provided beforehand. In reality the midterm exam is just another programming assignment that is worth more points. It will be due during the 11th week of the semester. Details will be provided beforehand.
Research Project
Overview
Each student will complete a research project in which they put in practice the tools learned over the course of the semester. The primary focus will be on managing the project in an automatic and reproducible way so that it can be shared with other collaborators. The project will be hosted on GitHub and will include the following:
- slides
- manuscript
- r code
- data (raw and tidy)
Students have two options regarding the type of project they do:
- Personal project (real)
- For advanced students working on their own data
- Ideal for QP, thesis, other projects
- Hypothetical project (simulated)
- For students w/o data
- Ideal for students in proposal phase (IRB, NSF, ect.)
All projects require the prior approval of the professor. Projects are due on the day and time of the university assigned final exam (though there is no exam).
Paper
The manuscript will be a write up of the methods/results sections of a research article. The focus is on clearly and accurately explaining the statistical analyses used in the project and appropriately interpreting the results. The paper must be a literate document written in Quarto or RMarkdown. We will demo this in class.
Presentation
Students will present their work in a semi-finished state during the final two weeks of the semester (10 min. presentation + 5 min. for questions). The slides of this presentation are part of the project and must also be hosted on GitHub.
Peer review
Each student is required to evaluate the project of two other students. They will fork the project in order to evaluate the reproducibility of the code and the statistical validity of the analysis. Students will write up two evaluations for each peer: one for the professor (not to be seen by anybody else), and one for the owner of the project in the form of a issue/comment on Github. The evaluation written for the professor should be longer and more in depth. It will be submitted via email. Both evaluations should be written in the style of a peer review for an academic journal, thus they should include comments, questions, suggestions, and constructive criticisms (#BeReviewer1). The point of this exercise is to help the author make the final product better.
Department rules and course policy
The course is designed to satisfy the learning goals of the Department of Spanish and Portuguese. More information available at: http://span-port.rutgers.edu/learning-goals
Communication
All course communication will be via Slack. You should have received an email with an invitation link to join the course Slack. Some rules for using Slack:
- Use an identifiable username and add your picture to your profile.
- Only the professor is allowed to use the @channel and @here mentions.
- While this is an informal communication channel, all rules of academic discourse apply.
- Ask and answer questions on the appropriate channel.
- Create channels as needed, especially for group presentations.
Attendance
Regular class attendance is essential for successful completion of the course. More than 1 absence will have a negative effect on your final grade. Arriving to class ten minutes late is considered an absence. The 2nd absence and every subsequent absence after that will result in the loss of 5% point off the final overall course grade, regardless of reason. Keep in mind that while you have 1 “free” absence, on the day/s you miss you will not be able to earn participation points, and you will miss the material given in class. If you are absent, contact a classmate immediately to get the assignments and to keep up with the material scheduled in the syllabus. The instructor is not responsible to put you up to date. Do not send emails to the instructor asking for updates if you missed class (i.e. “I was absent today. Did we do anything important?”). More information regarding the university policy on self-reporting absences is available here: https://sims.rutgers.edu/ssra/
Any planned absence that you are aware of ahead of time, such as religious holidays recognized by Rutgers University or Dean’s excuses, should be made up before the absence occurs. If you know that you will be absent, it is your responsibility to let the instructor know ahead of time. All holidays or special events observed by any religion will be honored for those students who show affiliation with that particular religion. Absences pre-approved by the RU Dean of Students (or Dean’s designee) will be honored. More information available here: https://scheduling.rutgers.edu/scheduling/religious-holiday-policy
Code of academic integrity
The professor will initiate an academic integrity case against students suspected of cheating, plagiarizing, or aiding others in dishonest academic behavior. Students are responsible for reading and understanding the Code of Academic Integrity.
Examples of academic dishonesty include, but are not limited to, plagiarism, cheating, and aiding and abetting dishonesty. An example of plagiarism would be to submit a written sample which in part or in whole is not the student’s own work without attributing the source. Cheating includes allowing another person to do your work and to submit the work under one’s own name. Any work which is submitted for a grade must be 100% the student’s own work. If you are not sure when it is appropriate to seek help, please see the professor.
Plagiarism is the use of another person’s words, ideas, or results without giving that person appropriate credit. Do not plagiarize.
Rutgers University Academic Integrity Policy: http://academicintegrity.rutgers.edu/
For more information
- http://academicintegrity.rutgers.edu/
- http://www.libraries.rutgers.edu/avoid_plagiarism.
Students with disabilities
Rutgers University welcomes students with disabilities into all of the University’s educational programs. In order to receive consideration for reasonable accommodations, a student with a disability must contact the appropriate disability services office at the campus where you are officially enrolled, participate in an intake interview, and provide documentation: https://ods.rutgers.edu/students/documentation-guidelines.
If the documentation supports your request for reasonable accommodations, your campus’s disability services office will provide you with a Letter of Accommodations. Please share this letter with your instructors and discuss the accommodations with them as early in your courses as possible. To begin this process, please complete the Registration form on the ODS web site at: https://ods.rutgers.edu/students/registration-form.