Kelsey Grinde (pronunciation) is an Assistant Professor in the Department of Mathematics, Statistics, and Computer Science at Macalester College. She earned her BA in Mathematics at St. Olaf College and her PhD in Biostatistics at the University of Washington. At Macalester, Kelsey teaches undergraduate courses ranging across the statistics curriculum, from introductory statistical modeling to advanced courses in mathematical statistics and her research area of statistical genetics.
Why did you decide to go into Statistics/Statistics Education?
This is a field that I ended up in somewhat by accident. I have always loved math, but found the first stats course that I took in high school to be pretty uninspiring (too much writing, not enough math!). I entered college with the intention of studying math or math education, with absolutely no interest in taking any further statistics courses. Thankfully, my advisor encouraged me to take a course in Statistical Modeling. The focus on real-world applications, modern computing, and careful communication, all within an environment emphasizing active learning, totally changed my mind about statistics. Following that up with a course in statistical theory (a perfect course for a pure math major like myself with a newfound interest in statistics) and a summer research experience in statistical genetics (which inspired a research trajectory that continues to this day) cemented things for me. Huge thank you to my undergrad research mentor and the faculty at St. Olaf who helped me see how cool the field of statistics is and set an example of the type of excellent teaching to which I now aspire!
What's a class/workshop at your workplace/university that you wish you could take and why?
My colleague, Leslie Myint, teaches a Causal Inference course at Macalester that I would love to take. Interesting questions and problems related to causal inference come up a lot in my research in statistical genetics. For example, I'm currently working on a project related to collider bias, which was something I never learned about (or, at least, don't remember learning about) in the stats courses I took in college or grad school, and I wish I'd known about it sooner. I routinely find myself recommending the class to students, and I'd like to follow my own advice and take it as well!
What is your go-to source for data?
One of my favorite sources for new data is my students! Many of them find or collect data relevant to their research positions, internships, honors projects, or personal interests that end up leading to really great final projects. It gives me a chance to learn about their other academic interests and to find out about cool research happening on other parts of campus. (That said, I'm really excited to go read all the other Meet a Member posts and find out what others have answered here! I'm always on the lookout for new, interesting data.)
What do you enjoy doing when you’re not working?
I enjoy all things related to soccer, especially playing against Macalester students in our college intramural league and cheering for my local MLS team (go Loons!). I'm also looking forward to watching the Women's World Cup this summer!
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