This course will guide a cohort of Data Fellows who serve as research assistants in labs that apply statistical techniques to a domain area. It will offer extra training in applying statistical skills as a part of a larger research effort.
In the course, Data Fellows will present statistical analyses, methods, questions and challenges from their ongoing research. They will give and receive feedback that will help them apply statistical methodology to their research; they will deepen their knowledge of statistical and computing methodology on topics relevant to the research of all participants. Data Fellows will learn about best practices and soft skills to perform statistical consulting and to work collaboratively.
If you have questions, please contact advising@stat.wisc.edu.
You must have the course requisites (see below) and fill out this form here before being considered for enrollment in this course.
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Course description
Students will serve as “Data Fellows” in their research groups, where they apply statistical techniques to a domain area. In the course, they will present the statistical analyses, methods, questions and challenges that they are working on as part of their ongoing research. Students will give and receive feedback and advice that will help them make progress on their research, such as on appropriate methodology they could use in their application problem. All Data Fellows will deepen their knowledge of statistical and computing methodology on topics that are relevant to the research of participants. Readings will be adapted to target these most relevant topics. Data fellows will learn about best practices and soft skills to perform statistical consulting and to work collaboratively.
Data fellows will write a report about the statistical analyses used in their research, including a self-reflection on how they expanded and improved it as a result of the course. Grades will be based on participation (quality of feedback and peer-review of final reports) and on the final report.
Requisites
- 1 programming course (CS 200, CS 220, CS 300, CS 320, or CS 400), and Statistics / Data Science modeling (intro Stat + STAT 303 + STAT 333) or (STAT 240 + STAT 340), and Junior standing or above
- and, via consent of instructor (fill out this form to ask for instructor consent):
- concurrent research experience (enrollment for independent research credits or employment as a university student paid hourly) focused on performing statistical analyses with a non-statistician mentor.
- agreement by the research lab PI that the student can share details with other course participants and instructor so as to receive feedback and advice, such as the study question, the experimental design, a presentation of the data and results.
Learning outcomes
- Learn communication skills with statisticians and non-statisticians
- Explain statistical concepts to researchers in their domain
- Improve the quality of research in your lab, including appropriateness of method choice, effectiveness, and reproducibility
Guidance for joining a lab
To benefit the most from this course, it is critical to have access to real data and meaningful scientific questions. Being a member of a campus research group is a prerequisite for course enrollment.
If you are just beginning your journey in undergraduate research, we recommend that you refer to resources:
- finding a research mentor
- how to find and enroll in research opportunities
- undergraduate fellowships and summer programs
- guide to research At UW–Madison.
- list of departments/faculty who are looking for help with analyzing data (note that you must be logged into your wisc google account to access this information)
When seeking a position, try to identify labs aligned with your interests, communicate in a way that highlights your unique skills, and evaluate offers using relevant criteria. The resources above offer guidance for each step, including workshops and staff contacts for personalized assistance.
In the context of this course, you should prioritize projects where the data and scientific questions are already available. It is okay if the data are messy or in a format that you have not encountered before — in fact, this often makes projects more exciting. To identify labs that emphasize data analysis, consider attending the Statistics Department’s Undergraduate Research Lightning Talks, where faculty overview their research and describe open positions. You can also explore the Data Science Institute’s community map, which features the profiles of data-oriented researchers across campus. Finally, once you have a research mentor, ensure that you will be able to share intermediate findings with course peers and teaching staff.
Frequently asked questions
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How do I get permission to enroll in this course?
Besides the requisites above, you will have to fill out this form for us to verify you have taken the requisite courses and to tell us who you are working with.
When will I receive permission to enroll in this course?
We will start the reviewing process April 22, 2024 and you will be notified about a week after. Since this is the first time this course is being offered, we do not know how high the demand will be for this course. Preference will be given to graduating seniors.
If the course has not filled during the first review of applicants, we will continue to review once a week until the course fills.
I read through this page and I still have questions
If you have a question that was not answered on this page please contact advising@stat.wisc.edu.