Conner Jackson is a Research Instructor in the Department of Biostatistics and Informatics at the Colorado School of Public Health. He serves as the chair of the Education Committee for the Center for Innovative Design and Analysis and teaches a 6-week short course about statistics and data science to bench scientists. His research focuses on the analysis of correlated data, largely in the context of infectious diseases.
Episode Description
Returning guest Conner Jackson walks us through a day in the life of the education and early career of a biostatistician.
+Full Transcript
John Bailer I'm John Bailer. Stats and Stories is a production of Miami University's Department of Statistics and media journalism and film, as well as the American Statistical Association. Joining me as always is regular panelist Rosemary Pennington from the media journalism and film department. Our returning guest today is Connor Jackson. Jackson is a research instructor in the Department of Biostatistics and informatics in the Colorado School of Public Health. He serves as the chair of the Education Committee for the Center for Innovative Design and Analysis. And he also teaches a six week short course about statistics and data science, the bench scientist. His research focuses on the analysis of correlated data largely in the context of infectious diseases. But we had him on to talk about a weather turtle last time. So Connor, one of the things that we got to start talking about, and we read about your pH row to the tortoise story, you mentioned that it's not like some of the other work that you've done, that your day to day job might have you working on a variety of other topics. I was just curious what day to day looks like? And how did you get initially involved in this?
Conner Jackson
Yeah, absolutely. So my background is actually in microbiology. And so originally, I planned to go to med school, and I got to undergrad, and I got into a research lab right away. And it was just fascinating. I always knew that I liked writing. And obviously, I have a strong interest in it. So it seemed like an obvious choice. I actually switched my major very quickly into undergraduate coursework and focused more on microbiology because I thought I would be a research immunologist in the lab that I got into. And then as I sort of got through undergrad, I enjoyed the research process. But I was feeling a little bit unsure of where I wanted my career to go. As many folks do in their undergraduate, I went to career counseling. And it figured out based on my skills, was that a career in biology, statistics, and anthropology would be kind of my top options. From there, I kind of realized, well, that sounds a lot like epidemiology, right? So I started there, and I started just talking to anybody who would have an hour to talk to me. And I think that was something that I learned very quickly. It was like, generally people will make time if you say, Oh, I'm interested in what you're doing, generally, people would be more than happy to talk to you, at least in an academic setting. And so that was where I started. And I just talked to anybody who had time. And ultimately, what drew me more towards statistics in general was I just, I'm interested in so many different things. And the ability to kind of do whatever is interesting to me was super appealing. And then the other thing that I learned in my undergrad was that I loved being a resource for people. So I worked in student government, and I loved when people would come and sort of say, like, hey, I need help finding this, this or we did a lot of mental health work. And the fact that I love being a resource for people and the fact that I am interested in so many different things, just by biostatistics was just such a glaringly obvious career path. And that was kind of where I went from there and then started an MPH and biostats program, and then just did really well in the coursework, they recommended that I switched to the MS and biostats, and took a year off and started working as a sort of consulting statistician, and that's the position that I have now. So that's sort of a longer background. But the point that I want to make is that, from a day to day perspective, what I do now is many things that I'm interested in. So I was able to maintain a relationship with my former boss that I worked with in an immunology lab where we do a lot of malaria research. So I still work with her. But I also was able to take on some other work doing HIV research, and then also doing Emergency Medicine Research. And so I think the important lesson about statistics is that the math, the underlying math, doesn't change, right? So that's what I really, really love about statistics is, you know, whether or not I'm doing a t test for malaria research, or HIV or education research, it's still a test.
Rosemary Pennington So Connor, you mentioned that sort of writing is something you're interested in, too. And I wonder how you've approached sort of how you write about statistics and how that might have changed as you sort of continue to explore this particular field?
Conner Jackson Yeah, I think that for me, something that I've really struggled with actually is figuring out how to translate statistics in a meaningful way to non statisticians, as a consulting statistician and as a research instructor at the university. It's nice that I have sort of a cohort of statisticians to interact with, but most of my interactions are with non statisticians. And so I think that whether it's just reading reports or reading manuscripts really being intentional, and again, sort of thinking about what I learned from the petro article, like taking a step back and really being thoughtful about out, how does how does someone who's a non statistician, how will they likely interact with this, but also knowing that, because I came from a bench scientists perspective, I kind of understand a little bit about what people are working with and what their familiarities are with statistics. And obviously not saying that all bench scientists are this. But you know, you sort of get a sense of what people's familiarities are. And from there, being able to contextualize things in a way that's interesting to people I think, has done wonders as far as kind of improving the efficiency with which we can cut output results.
John Bailer
Yeah, well, thank you so much, Connor. I'm afraid that's all the time we have for this episode of Stats and Short Stories. Stats and Stories is a partnership between Miami University’s Departments of Statistics, and Media, Journalism and Film, and the American Statistical Association. You can follow us on Twitter, Apple podcasts, or other places you can find podcasts. If you’d like to share your thoughts on the program send your email to statsandstories@miamioh.edu or check us out at statsandstories.net, and be sure to listen for future editions of Stats and Stories, where we discuss the statistics behind the stories and the stories behind the statistics.