Reflections on SAMSI’s 2018 Undergraduate Modeling Workshop

Alex Hayes

Alex Hayes, Statistics Major, Rice University

The following is an extract from the Blog of Alex Hayes.  To view the entire piece, visit his blog.

I spent the last week at Statistical and Mathematical Sciences Institute’s (SAMSI) undergraduate modeling workshop. This year the workshop was hosted at North Carolina State University (NCSU) in Raleigh, NC.

The Rundown…

 About thirty students attended the workshop. To get in there’s a mellow application process. SAMSI covered travel, rooming and food for the participants. We were expected to bring laptops with R and RStudio installed. The purpose of the workshop was to give undergrads experience modelling real world data. Each year the workshop has a different theme, in our case statistical analysis of climate phenomena.

Before the workshop, we choose from a list of six projects for the week. On Sunday night, we flew in for a welcome dinner and met the other students on our project team. Each group had a SAMSI postdoc as group leader.

On Monday Doug Nychka and Chris Jones gave us a broad overview of the statistical issues present in climate science. We spent the afternoon doing some team building activities, discussing our interests, what skills we brought to our respective groups and developing research questions.

We spent the next three days working on our projects. We probably spent six hours a day modeling, and an hour or so at a research presentation or R workshop, and an hour goofing off and hanging out. The talks in particular were very good, presenting current research at the undergrad level in an engaging way.

In the evenings a small group would normally explore the bars in the NCSU area, which was nice after a long day on campus. The workshop concluded on Friday, when each group presented their findings before flying out in the afternoon.

“Personally, the workshop enabled me to make some valuable connections within the stats community.”

The Workshop…

 My group was led by Mikael Kuusela, who did a fantastic job helping my group find research questions. He gave us a ton of individual feedback and was very attentive and patient. I particularly appreciated his advice on choosing questions that scientists care about.

Personally, the workshop enabled me to make some valuable connections within the stats community. At the end of the workshop, Mikael asked me if I’d like to write up a short outreach piece based on my project with him, which I’m super excited about. Keep an eye out for an upcoming piece on a functional decomposition of ocean thermoclines during El Niño (feat a plot we’re calling The Bananafold).

Earlier this year Maggie Johnson, another SAMSI postdoc, put me in contact with some of the bioinformatics crew at Pacific Northwest National Laboratory and I nearly ended up taking a year off to work on omics projects with them.

I also had a blast getting to know Doug Nychka. Not only was Doug super patient with my many newbie questions about GAMs and splines, it was fun to chat with him about climbing and the UW-Madison statistics program.

 

Courtesy of Alex Hayes_at_samsi

Alex Hayes (middle) is joined by fellow Rice University Data Science Club members at the 2018 Undergraduate Modeling Workshop, May 21-25. Hayes influenced several of his fellow club members to apply for the worthwhile SAMSI workshop. (Photo courtesy of Alex Hayes)

Perspective on the Undergrad Stats Community…

As someone who’s spent a bunch of time organizing undergrad statistics activities over the last year, the workshop was an interesting opportunity to learn about the broader community of statistics undergraduates. Here are some of the notes I took.

We have fundamental misconceptions about the purpose of modeling: When groups presented their initial research questions, it was immediately clear that many students were conflating descriptionprediction and causation. Throughout the week, there were many attempts to turn everything into a prediction problem, or to interpret descriptive analyses as causal.

The pre-requisite stack is not very deep: Most students had taken a mathematical statistic course, but very few had much coursework beyond that. Less than half the workshop had background in linear regression, and people were much less comfortable with linear algebra than I would have expected. Barely anyone had probability or analysis background.

Programming skills are rate determining: We dramatically overestimate our R capabilities. In particular, non-tabular data really threw people off. My group took about three days to calculate mostly summary statistics and make basic plots.

Everybody’s resume looks the same: I’ll write more about this soon, but everybody advertises themselves in exactly the same way. This is despite having wildly varying skillsets. As a job seeker, how do you demonstrate that you are on the upper end of the competency spectrum? As a recruiter, how do you differentiate between candidates who look identical?

That’s a Wrap…

 We learned things at a great workshop. Everyone should go if they get a chance. The statistics community should spend more time teaching beginners about the big picture: what statistics is and how we should use it.

Rutgers Undergrad Challenged to Succeed at Modeling Workshop

Riya Prabhaudes1

Contributed by: Riya Prabhudesai, Math and Physics Major, Rutgers University

The SAMSI Undergraduate Modeling Workshop was an amazing learning experience that I will never forget. A series of collaborations with postdoctoral scholars and a diverse group of undergraduate students, lectures given by field experts, educational workshops, and a poster session, created for a greatly productive week for me.

Getting Started

The first few days were more intense and packed with educational material than I had initially expected. We received an in-depth yet broad overview of the field of climate science, as well as mathematical and statistical methods that helped analyze the problems in climate change. This was accomplished through workshops that dealt with coding in R software, as well as presentations given by the program’s coordinators and guest speakers.

I appreciated that despite being undergraduate students, our inexperience in the field did not translate to an inability or ineptitude in the mentors’ and coordinators’ eyes. This empowered us to take on challenges that seemed overwhelming and unattainable in the span of a week — I was never told that I did not have the ability or brain power to solve a problem. Not only were the postdocs and program coordinators extremely encouraging, but the undergraduates that I worked with and talked to were helpful in any way they could be, and came to the workshop with a desire to learn.

Being in this environment motivated me to delve deeper into the project I was working on with my group throughout the week, while also giving me a list of papers and topics in math that I wanted to learn more about when I got back home.

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Rutgers University Undergraduate, Riya Prabhudesai, presents her research for her group project during SAMSI’s Undergraduate Modeling Workshop from May 21-25. Her group presented statistical research on vegetation through data captured by remote sensing methods.

Hard Work Pays Off

Although the workshop did prove to be intense and tiring at points, there was room for downtime with other students in the program. We ventured into downtown Raleigh area a few nights, as well as went on a few short walks around the NCSU campus itself. At the end of the week, we were able to exercise our presentation and communication skills through a 25-minute research presentation documenting the work we had done and problems we had solved throughout the week.

While the presentation in and of itself was a difficult task to finish, it served as a memento of all the work we had put in throughout the week. Through the course of a week, I learned how to implement various statistical and mathematical methods in R, and apply these techniques to analyzing complex climate systems. I caught a glimpse of the intricacy and thoroughness scientific research requires, and would recommend this workshop to anyone that has a vested interest in the mathematical sciences, as well as the subject material the workshop puts out every year.