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ASA REU Experiences Offer Students Value

1 September 2018 No Comment

Mark Daniel Ward

In the April 2016 issue of Amstat News, we announced that the ASA received a three-year National Science Foundation (NSF) grant to establish a series of Research Experiences for Undergraduates (REUs). Three such REU experiences have been offered during each of the previous three summers, with four students per site.

With this issue’s theme of “training the next generation of data scientists” in mind, we encourage faculty members to apply for their own REU site.

From left: Ellen Kulinsky, University of California, Berkeley; Sastry Pantula, Oregon State University; Aaron Huang, University of Washington; Betsy Hensel, University of Virginia; Shelby Taylor, Brigham Young University Photo by Megan Griffiths

From left: Ellen Kulinsky, University of California, Berkeley; Sastry Pantula, Oregon State University; Aaron Huang, University of Washington; Betsy Hensel, University of Virginia; Shelby Taylor, Brigham Young University. Read more about the OSU REU program2017 Photo by Megan Griffiths

Only a few sites in the Mathematical Sciences are dedicated to statistics. Similarly, encourage your students to apply for REU opportunities; the full list is available.

ASA REU Experiences
2016
Summer Program in Research and Learning (SPIRAL) at Morgan State University, led by Monica JacksonData Science for the Public Good (DSPG) at Virgina Tech, led by Stephanie Shipp

REU at Lamar University, led by Kumer Das

2017
Oregon State University, led by Thomas Sharpton

Emory University, led by Lance Waller

WINona STATe StatisticsREU (WINSTATS-REU), led by Silas Bergen

2018
Colorado State University, led by Julia Sharp

The University of North Carolina at Greensboro, led by Sat Gupta

Summer Program Advancing Techniques in Applied Learning of Statistics (SPATIAL-Stats) at Morgan State University, led by Leon Woodson and Monica Jackson

Students at the ASA REU sites are participating in research that run the gamut, from theoretical to applied to data-driven topics. For instance, Julia Sharp and her colleagues at Colorado State University designed projects for the students that included the exploration of anticancer agent properties, classification of salmonella serotype proteins, and simulating and examining optical density versus time data from particles under varying experimental conditions. At Morgan State University, Monica Jackson and Leon Woodson built on the years of success of the SPIRAL team to host the first Summer Program Advancing Techniques in Applied Learning of Statistics (SPATIAL­Stats). Their goals included developing and analyzing spatial statistical methods that will detect geographic distributions of populations at risk, determine cancer rates, and define environmental conditions that affect diseases.

I just returned from a visit to see Sat Gupta at the University of North Carolina at Greensboro. He and his colleagues and students focused on developing and comparing predictive models for various diseases using machine learning and robust regression techniques. They also used publicly available epidemiology data for building predictive models. Gupta worked with students on methods for ensuring survey respondents have confidentiality in their responses using randomized response models.

When I was talking with the students over lunch at UNC-Greensboro, I was particularly impressed to hear about how deeply they dived into their research projects. Throughout our meal, the students discussed the pros and cons of randomized response models with such confidence that one could easily have thought the models were all originally developed by them.

These students spoke about probability and statistics as if they were already in graduate school.

I was also struck by the degree to which the students appreciated the underlying statistical theory. For example, Purdue student Amber Young opted to work on two research projects over the summer. Amber was my student in a probability theory course a couple years ago, and I remember she enjoyed probability theory. Nonetheless, as we sat at lunch and discussed her summer experience, I was impressed with how comfortable she and the other students were about certain probability topics we usually don’t cover until the PhD-level course. I brought up a few qualifying exam questions with the students, just to see how they responded. These students spoke about probability and statistics as if they were already in graduate school.

In many cases, students travel to other sites during their REU experiences (e.g., field trips to federal research laboratories, research conferences, companies (such as SAS), and other institutions) as part of their professional development experience. The REU sites are intended to foster the full career development of the student. With this in mind, I asked some of the students to reflect on their experiences over the years. Speaking about her participation from summer 2017, Zavia Epps said, “I had a really great personal and professional experience during the REU I participated in last summer at Emory University. I had the amazing chance to learn a lot about biostatistics and, truly, I think it is an amazing field—career and education wise.” She continued, “Being with Dr. Waller and the department of biostatistics at Emory was really great, and I really liked every moment of it.”

My colleagues and I believe the ASA REU experiences are valuable for students. We hope more faculty will apply to start their own sites. Kumer Das at Lamar University, as an example, had one of the pilot sites in summer 2016. Building on his experience, he applied for an NSF grant and was awarded with funding to start his own site at Lamar, beyond the ASA REU.

If I can assist colleagues in any way with their own proposal preparations for NSF REU sites, please reach out to me. REU programs in statistics have a tremendous student impact. We need more of them! Write to me, Mark Ward.

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