[TRANSCRIPT CONTINUES] Donna LaLonde: So how is it that you learn enough ecology to collaborate? Right, so I'm just always amazed at the language that there is within a specific domain. So how do you learn to talk to your collaborators? Erin Schliep: Yeah, sometimes I'm more successful than others, that's for sure. But you really have to want to be able to communicate, right? Because with those that are outside statistics, there are some statistics words that I definitely don't use when I'm communicating with them, and there's obviously things that in their world that they're not going to say to me, because I'm not going to understand it. But just continually asking questions. It's a back and forth. 'I don't know what you're saying,' and being comfortable saying 'I have no idea what you're talking about' just to be able to get them to explain it on a different level. And you have this in teaching as well, right, you have to read your audience and what parts are they picking up, where are they having questions, to try to explain it again and sometimes again and again. And I'd be the first to admit that in a lot of these topics... Had you asked me this before this project started, I knew nothing about nitrogen and phosphorus and lakes, right? So now I'm slowly picking up some of the terminology with nitrogen cycling and the importance of agricultural land, how it changes the levels of these nutrients. Just even the way that the data is being collected. For example, Secchi disks. It's literally a bull's-eyelooking disk that they drop into the lake when they're out on a canoe and they measure how far it goes down before they can no longer see it. Alright, so, that's the depth, right? Secchi disk depth, is what the column is listed as in my dataset, but had I not known that, that was just another variable. It's just from being interested in wanting to continue to learn. Like I love learning about some of these things I never would have explored prior to now. These are even things that you might not have learned just in your traditional environmental studies or environmental science classes. Because just some of it you learn when you're in the field. And I consider some of my collaborative conversations like being in the field. They're learning about some of these different technologies and different ways that they just talk about it. Lara Harmon: I love the tools scientists use. It's always really interesting to figure out how they do actually do stuff. Erin Schliep: Yeah, absolutely, yeah, and in practice, right? You ask them, you know, how accurate is that really and usually they have a pretty good answer on either, 'oh, pretty accurate' or 'ehhhh.' Some people are better than others. Lara Harmon: That's cool. I love that you just have to watch it. You're like, hm, can't see it. Alright, Donna, do you have any more questions before we move on? Donna LaLonde: Well, this is totally off the topic of statistics, but as a cyclist I'm really curious how far is your bike commute and what do you ride? Erin Schliep: Ah, great question, yeah. So my bike commute is currently about three miles up one very big hill on the way in and down one very big hill on the way home. Right now I just have a commuter bike, a Cannondale Quick 4 to be exact, but on the weekends when I actually have time to get out, I ride a Cannondale CAAD 10 road bike, so I'm of the Cannondale fleet right now. Donna LaLonde: Good choice. Lara Harmon: Alright, ready for the next one? Okay, so we've kind of moved a little bit into this, I think, but what is the coolest thing about your work and your research? Erin Schliep: Yeah, so we touched on that a little bit, because I think you can recognize I'm passionate about the collaborations and just learning about the different areas of science that statisticians are currently being involved in. Again, mine are primarily focused on environmental applications but they definitely wouldn't need to be. So some of these collaborations span from during my postdoc, I was working-sorry, my graduate degree, I was working on understanding or evaluating the condition of wetlands in northern Colorado. I've done some projects with people that are looking at social behaviors of dolphins and whales. Again, I don't know a lot about dolphins and whales other than what I've learned about through that project. A lot of the work I did when I was at Duke was looking at estimating carbon in forests in North Carolina. Another big project that I worked on in North Carolina was these people at NC State set up a bunch of camera traps, and these camera traps take pictures whenever an animal walks in front of it. And so it's a citizen science project where then people go in and they identify what species of animal it was. And they're interested in understanding whether or not different species were co-occurring, meaning that these species actually see each other on a day-to-day basis. We talked a little bit about the nitrogen examples. So I've talked with a lot of people that are studying limnology and I have collaborators up in Minnesota looking at fish populations, and so predator/prey fish populations and how those might be changing in some of the Great Lakes and the Midwest or Upper Midwest. And then those projects that stem from looking at air quality metrics from satellite data, right? So, again, there are so many different areas that statisticians can get their hands in, and you just continue to learn about areas of science that are so interesting. And you can still be passionate from the statistics side, you can apply it to whatever area you're just interested in. Out of all those projects, probably if I had to pick a favorite, and again I don't know if I can pick a favorite based on purely the stats behind it, but whenever you get the opportunity to visit a research site, that's fun, right? So now you can just see actually on the ground where these scientists are doing their studies, right? Where are their field sites? And so our team went down to Puerto Rico for a week during the winter-our winter-and it was beautiful, and we got to explore the environmental gradient across the island, right? You have the extreme sort of high precipitation regions in the Northeast, where there's the very dry region in the south. You can see how the vegetation there varies dramatically based on that elevation change and really how the systems come across that particular region. And so when we were there it was about a year and a half before the hurricane came through. And so after that hurricane, we were able to see some of the pictures afterwards and you really saw the devastation of the island that it incurred in that big hurricane. So again this sort of travel aspect, but in getting an opportunity to actually now spend time in the field with your collaborators that really know the environment and just get to tag along with them, that's pretty fun. Lara Harmon: I know someone who does that, so I've heard those stories. It always does sound like a lot of fun. Erin Schliep: Yeah, I don't know how long I would survive at a field research station, yeah. Cold showers only go so far for me. But it was definitely fun for the week that we were down there. Lara Harmon: And I just love to hear about scientists from non-scientists perspectives, and what they get up to. [TRANSCRIPT CONTINUES IN REPLY]

[TRANSCRIPT CONTINUES] Erin Schliep: It was an experience. We were out on a hike one day and a tree limb broke off of a tree that was near where we had been staying and it fell across the rental car, so there's a huge dent across the hood of the car. You get the whole experience of non-outdoor scientists... Lara Harmon: Yeah, I meant to say that. Non-field scientists and field scientists. Erin Schliep: And I was one of them. It was good, though. It actually makes you really understand what you're doing on a completely different level. And so really I would argue all statisticians should have a field day with every project if it's possible, to really see exactly how this process works. And that's actually some of the advice that I got from my adviser Jennifer Hoeting back in Colorado. She was getting opportunities to go out and tag the deer when they're studying chronic wasting disease. So now they're flying in on a helicopter and they're dropping down and they're collecting the data and they're tagging the animals. And this is not something you necessarily need to do to be a statistician, but I think it makes you really appreciate when you start questioning why they didn't do a better job collecting their data, you appreciate that it's not always possible to do so. Lara Harmon: I think that sounds like quite good advice, to have a perspective from all levels. Erin Schliep: Yeah, especially if you like to be outside, yes. Another reason why I'm in the environmental stats world. Lara Harmon: Makes sense. Alright, Donna, do you have any extra questions? Donna LaLonde: Nope, I'm good now, thank you. Lara Harmon: Alright, are you ready for the next one? Oh, I think we have covered a little bit of this one, as well. So what do you like to do when you are not working on research or teaching? Erin Schliep: Yeah, or riding my bike, yeah. I think just literally being outside and being active is what I do most of the time when I'm not sitting literally in this chair teaching my students. And so that includes biking, but running, hiking-I did a lot of hiking when I lived in Colorado, and even actually here in Missouri we have some nice hiking trails. I'm actually a golfer, so I spend quite a bit of time on the golf course when I can get away for an entire Saturday. It's a little bit harder for me to do right now then just going out for a quick run or bike ride, but playing golf is actually a passion of mine, as well. Donna LaLonde: Do you compete, Erin? Any running racing , or cycling racing, or duathlon, triathlons? Erin Schliep: Yeah, so I'm primarily a runner, when it comes to racing, and so I would say the half-marathon is probably a favorite. But I did run my first marathon-first two marathons, I guess-in 2018, and I'm looking forward to not running another one this year. But it was good. It was a great experience, and I think it's just if you are passionate about running, it's great to get outside. I actually do the sports of the triathlon, so I like to enjoy swimming and biking and running. But I've never actually competed and put them all together. I'm still a little bit terrified of the whole changing transition idea, but it will happen. It just hasn't happened yet. Donna LaLonde: So as a runner, I just have to ask, where were the marathons? Erin Schliep: Great question. So I grew up in Minnesota, and my parents met at University of Minnesota, Duluth, and so the first marathon I did was Grandma's Marathon up in Duluth, Minnesota. So that was just this past June. And about a month prior to that, roped in with some friends, here in Missouri I ran the Berryman Trail in south-central Missouri, part of the Ozark Trail. So that was a completely different experience, all single-track trail for 26.2 miles .At the end of that one I also said, I think this is a never again for me. But you never know. Again, it's fun. You're outside, you're being active, and so it's hard for me to say no to those types of things if the opportunity should come around again. Donna LaLonde: Yeah, I understand. The Grandma's Course is very beautiful, so that's wonderful. Erin Schliep: Yeah, interestingly enough, that's one of those races where you run right along Lake Superior the entire way. And probably about mile 16, you see the bridge which is downtown Duluth, and that's sort of the iconic sort of symbol of Duluth, and you see it for 10 miles running toward it. Although the marathon 2018, it was 50 degrees and foggy. Never saw the bridge, barely saw the lake, and so, totally different. Don't know if that's helped or hurt that. So the running conditions, the temperature was perfect, but it wasn't maybe the exact experience that people have had in the past. Maybe why I'm thinking about doing it again but, again, not this year. Lara Harmon: I've watched runners get other people to run. It's hard to say no. Erin Schliep: It very much is. It's easy to get people to commit to it because you just tell them how great it's going to be and the competitive nature I think jumps in that you're like, okay, let's all just do it, and you sign up, and now you're doing back-to-back races and the excitement gets you there and the adrenaline gets you there. Lara Harmon: Donna, do you have more questions? Donna LaLonde: I am not going to start down the running path or we would be talking about our favorite races for the rest of the day. Although I have to say that I'm liking the trails a lot these days, so I totally advocate another trail race for you. Erin Schliep: Yeah, absolutely. It's a different deal altogether, a different mentality, different competitive component to it. I definitely don't race those as seriously as I would race a road race, so it's much more for the social aspect for me and I think that's probably a healthy way as we get older Lara Harmon: Okay, are you ready for the last one? Okay, what question that we didn't ask would you like to answer? Erin Schliep: Yes, so the one thing I think that's important to know is that even though this entire interview or discussion so far I've been talking about environmental statistics, you definitely as a student or as someone coming up into this career of statistics and applied statistics in general, is that you definitely don't need to stick to one. And it's interesting how similar they are. The question would be are there opportunities for statisticians to work in more than one area? So not just, say, environmental statistics. And the answer is absolutely yes. And it's amazing to me even as I have continued my career to see some of the connections from different areas. We have, obviously, seminar speakers come through the academic setting all the time. You see some talks that aren't in your application area that are definitely tied to or somehow tangentially related. And so some of the work that I've done with, say, dolphins and whales borrows from the idea of social networks, which then extends into looking at Facebook and Twitter and how those sort of social networks have evolved or changed through time. Currently at Mizzou we're working on developing a sports analytics program. And so you might say, environment, sports, right, I don't see the connection. But think about animal movement models. We watch geese fly, right? We watch animals move across the landscape, and they're responding to one another. Same thing as soccer players as they run around a soccer field, alright? So how can we borrow and look at some of the models and methods that we've used from one area and notice that they directly apply to other areas. Looking at some sort of different objective, where animals might be trying to pursue higher ground or food, and soccer players are trying to get a ball into a goal, alright? And so a lot of these areas, it really simmers down to take that maybe one step further. Much of the methods that have been developed even in the past 10 to 15 years in spatial and spatial temporal stats have dealt with big data, so high frequency time series data or spatial temporal data that have been collected and how to monitor those or model them. And you can take that and now think about athletes. And you've got the GPS trackers on them, you've got their heart rate monitors on them. There again is a high frequency time series data on these individuals as they run around a soccer field, and how their heart rate or other biometrical things are responding. That extends right into precision medicine, right? How should we be training our athletes in order to tailor their programs and their covering to increase the performance of both the individual and the team. And so there are so many connections between all these different areas as you start learning more and sort of building up this toolbox of methods and models to use with them. It's very easy to start seeing some of the connections. So there's no reason to just stay in environmental stats if you have passions across as many areas as you want. So I'd sort of argue that if I wanted to get back into accounting there are ways to start thinking about the current experience I have right now with, you know, forest biomass, right? Some of the methods and models and things I've learned from these particular experiences and opportunities, I think, can directly relate into another future collaboration that might come knocking on the door. [TRANSCRIPT CONTINUES IN REPLY]

[TRANSCRIPT CONTINUES] Donna LaLonde: So, Erin, as you're describing these various projects, that actually makes me think about a question about-it's clear that that you use computational tools, and you talked about database, and So I'm wondering if you have any advice for folks in terms of, like, programming languages, database skills, that that they should acquire early on in their career. Erin Schliep: Yeah, so it's interesting. I mean, the times have definitely changed. When I graduated with my undergrad, I had never programmed up just a traditional regression model using software at all. The times have definitely changed. Our undergraduate students now are being sort of thrown at R and SAS and all the different tools like that. I say, currently, at least in the academic setting, R as a computing language is probably the most important, but really if you know one or you have the ability or you've experienced learning one, I'd like to say you could more easily-I don't say easily, but more easily-pick up a second and a third and a fourth... And it seems like right now I would probably argue that Python is becoming one of the most popular second or third languages to be learned. But again it depends on what your future direction is going to be. I know that SAS is still a big component when you think about from the medical arena or even industry jobs definitely want to see some SAS experience. And so I definitely would focus on just one, but start building up at least the walking knowledge of a few more if you can. But particularly as an undergrad if you walk out of undergrad feeling pretty comfortable in one language, I think throughout your graduate career you'll be able to learn the other ones as you go and as you need to. Again C or C++ definitely comes into play with big computing, but I think Python is really maybe where that's turning now. Lara Harmon: That's a constant topic of discussion that I see in our online community and elsewhere. Which languages to use and learn and for what. Erin Schliep: Yeah, and it's actually hard, and we talk about that even as a faculty a lot, of what languages we should be teaching our courses in. Because again if you're going to stay in academia, R sort of seems to be the one, and again, Python as an extension would be great, but if you're going industry or government than SAS becomes the way. And tailoring your classes appropriately becomes sort of an important aspect, as well. Donna LaLonde: So that makes me think we should have asked what's your favorite class to teach. Erin Schliep: Oh, wow, great, yeah. Oh, good one. Donna LaLonde: Like picking your favorite child, right? No? Erin Schliep: No, not at all, not at all. I really like teaching the applied regression classes. So applying your models, statistical models. Currently I'm teaching spatial stats, which, again, is where some of my research interest and passion lies, and so that's obviously been just a fun class to teach, just because I have a lot of the examples that I've mentioned while talking to you all that fall in that area. But just I would argue that the applied statistical modeling class is probably my favorite. And it's an Rbased class and so some students have some R experience and some of them are brand new, and so it's definitely a challenging class. The teacher in that aspect is giving enough example code to see what we're trying to do. But definitely it's not a matter of just hitting run on the code to make it work, it still takes the students quite a bit of time and effort to get the code tailored towards what they're needing to do in their labs and in their homework assignments, yeah. But I think maybe not in terms of particular class, but just in terms of students, I teach a lot of undergraduates and a lot of graduate students, non-statistics-seeking students, so I have a lot of masters and PhD students from the environmental sciences and really just across the university-quantitative psychology, etc. And so it's been fun to also then just continue to extend some of these collaborations and learn about what they're working on, as well. And so that's just been a fun way to meet more people across campus. Donna LaLonde: Well, this has been great! Thank you so much. Erin Schliep: Absolutely. Thank you for taking the time to chat with me. [END TRANSCRIPT]

[TRANSCRIPT CONTINUES] Donna LaLonde: And just so I understand. A water violation, that would be some kind of contaminant, something found in the water that is not good? Ruby Bayliss: Correct. Yeah, so it's a health-based water violation, and those standards were created by the Safe Drinking Water Act of 1974. And so anything that violates any of those standards counts as a water violation, whether that's contaminants getting in the water, how the water is being treated-because you know we have to treat the water with chemicals-and so are those at safe levels. And of course there's other factors that are involved, but those are the the main ones. Donna LaLonde: Well, that's great. And Loni, I know you're supporting this research and guiding this research, but maybe you may want to add your take on this, but also I know that you have lots of other interesting projects that you've been involved in. So what's the coolest? That's like I'm asking you to pick your favorite child but, well. [laughs] I'll put you on the spot. Loni Tabb: Well, I will say I think the coolest thing about the research that I do in general is the autonomy to research the public health challenges that really mean something to me. And so, Ruby mentioned her work in looking at water violations, when Ruby came into the PhD program, I spoke with her about her interest and what motivates her in the field of biostatistics to research the types of problems that really get her going. And one of our early discussions that came up dealt with the Flint water crisis. And so that's why she is now on this path of looking at county demographics and whether or not that can predict if you see water violations in a given county. And so for me the work that I do, it spans from focusing on say health disparities in-it could be a lot of different health outcomes, but in particular cardiovascular health in this country to all the way to social disparities in cities and whether or not alcohol access promotes more violence. And so there's a wide variety of the types of projects that I work on, but at the end of the day, I think the coolest part is that I'm incorporating space and I'm incorporating time. So where you live, where you work, where you play, where you learn, where you worship, your environment, it has a lot to do with different health outcomes that you might experience. And so I think with space and with health and with time, to be able to see over time what's going on with different health outcomes. And I think that that matters a lot. And so going into my training, I knew that I wanted to look at health-based things, I just didn't know what that actually looked like. And so in my training I focused a lot on mapping and measuring different disparities, and so a lot of the work that I'm doing is still grounded in that, and Ruby-I think it was such a nice match in terms of when she came into the PhD program, that her interests in at least what happened in Flint, Michigan, it's grounded in place-based circumstances. And so I think it's an important lens to look at different public health challenges. So I think that's the coolest part. Donna LaLonde: Could either of you say just a little bit about the tools that you use for your research? Loni Tabb: Yeah. So, for a lot of the place-based work that I do that speaks to the mapping and the measuring of things, I use R. R is a really useful and freely available platform, a statistical software package, that you can do a ton of very-from the the most simple type of statistical analyses to even the more complex. And I have other statistical software packages that I know of and that I use, like SAS, but R is like no other. They don't pay me to say this, I'm not employed by R! But, yeah, that's my primary tool that I take advantage of. Donna LaLonde: Sound like I could surmise that there might be a bit of advice there, learn R. Loni Tabb: Yes, yes. [laugh] Lara Harmon: For anyone listening, they have really good stickers, too. Loni Tabb: They do! Donna LaLonde: They do, they absolutely do. And if you develop a package and you get to name it, then sometimes you get to design the stickers. Loni Tabb: That's right, that's right, yes. Lara Harmon: And the community seems generally very active and interesting Donna LaLonde: So I think I've I've come to the conclusion that we all like stickers. So let me broaden that a little bit and ask both Ruby and Loni what do they like to do when they're not working or teaching or doing biostatistics? And Ruby, I'll start with you. Ruby Bayliss: Okay, no problem. So when it's warm out, I love to go hiking and I just love just being in the outdoors and being away from the city and just enjoying, yeah, more a rural setting. Actually as a kid I was fortunate enough to spend my summers at a lake cabin so I loved being at the lake, and I also loved going to beaches. And originally I'm from Minnesota, so obviously we're pretty landlocked, but we have lots of lakes. And so that's nice, but, definitely, whenever I've experienced the ocean, I've loved it. And so that's definitely one of the things that I was excited about moving to Philly for-well, obviously, besides the PhD program-was being like within like a two-hour drive to the beach. So I'm really looking forward to spending some time outdoors. And then also when it's colder, I actually really enjoy going to movies. Movies are great, and I think one of the things that I really like about movies is it really changes your perspectives. It just really changes your perspectives on different situations that people are put in, and it just is very eye-opening and a lot of thought. And I think even poorly designed movies can evoke different emotions to different audiences, and I think movies are just so relatable and they're just-I don't know, they're just special. Donna LaLonde: You want to give us a recommendation? Anything that you've seen recently? Ruby Bayliss: So unfortunately I haven't gone to see a movie in a while, but... Donna Lalonde: That's a good graduate student response. Lara Harmon: Oh, no, movies are how my sister got through grad school, I think. Ruby Bayliss: No, I usually try to go at least once a month, but I'm trying to think what was the last movie I saw... Well, the last great movie that I saw was actually Hidden Figures. I love that movie. I know it's not in theaters anymore, but it's just such an inspirational movie. It was just so well done. [TRANSCRIPT CONTINUES IN REPLY]

[TRANSCRIPT CONTINUES] Donna LaLonde: That's a great recommendation, yeah. Alright, Loni, when you're not at work or teaching, what is it that you like to do? Loni Tabb: I like to spend a lot of time with my family. I have two little ones, a seven-year-old and a four-year-old, so they keep me very busy. And especially during the summer months, we like to go to the beach and we like to hang out outdoors. I am a city girl at heart, but I like to be outdoors. But that's within certain boundaries. So I love to also go out and eat. I'm a foodie. And so I like to try a lot of different types of cuisines. So I grew up in a Caribbean household, and so I have a lot of bias towards spicy food and Indian food, West Indian food, and so I try to find foods from other cultures that kind of mimic that. And then I am heavily involved in my church.And so I run this ministry at my church called MOPS, it's Moms of Preschoolers, and so it's for moms that have little ones, that they either are members at our church or they're in the community. And we meet up once a month and we do different activities. Sometimes we do volunteer activities, but other times we just simply color. That's what we did last month. So those are some of the things that I like to do when I'm not trying to address some of these different public health challenges that we face in the world. Lara Harmon: I have gotten together with my friends and just colored, too. Loni Tabb: Yes, it's very therapeutic. Very therapeutic. Donna LaLonde: So if a person is visiting Philadelphia, what's the have-to restaurant recommendation, from the foodie? Is that too difficult to choose? Loni Tabb: No, no. I mean, I'm biased, right, so I will say this-if you come to Philadelphia and you are looking for some traditional Philly food you have to get a cheesesteak. And you could get a chicken cheesesteak, a veggie steak, or a regular cheesesteak, and I think the best place to go to get that is... Hm. Which one? Hm-hmm-hmm. I think Delessandra's. That's the best place to go and get steaks in the city. Traditionally speaking, people, when they come into the city, they go to South Street and they go to Geno's or Pat's. Those are very popular touristy steaks. But I don't think that they're like traditional steaks. They're, you know, they're touristy steaks, so if you want the real deal, you have to go to Delessandra's. Lara Harmon: I actually just wrote that down because I know we're going to Philly in a few years for a conference. I'm always like, is there food I can pick up and carry? Donna LaLonde: Yep, that's wonderful. Okay, so our last question for both of you is what question didn't we ask that you would like to answer? So is there something, some area of your research or work or play life, that you would like to share with us that we didn't ask in a question? And Ruby, start with you. Ruby Bayliss: So, I actually had a hard time thinking about this question, because I feel like the questions that you already asked were pretty broad enough to where I could express stuff that I felt without you really directly asking. So I'm sorry, but I'm going have to pass on it. Donna LaLonde: Totally fair. Loni, how about you? Loni Tabb So I, too, struggled with this a bit, but a question that I actually came up with, and you guys have the answer, is how do we best ensure we increase diversity in the biostatistics/statistics field? And well, the reason why I say you guys have the answer is actually through initiatives like this. Ensuring, you know, promoting a field, right, it's almost like our duty to show or at least try to show the representation in that field. So ensuring that women and minorities know that this field actually exists and that it's open to them through initiatives like this, and seeing women and minorities talk about this field, creates a certain picture that the field is actually for everyone and not just a select few. And so I was really happy to hear about this initiative and about the push to kind of get folks out there so that people know that the field is growing, and it has been growing. We still have a ways to go but I think things like this allow folks coming up to know that they belong here. So you guys had the answer. You didn't ask the question, but you have the answer. Donna LaLonde: Oh, well, only with your help, that's for sure. Lara Harmon: Oh, I completely agree. I think that's extremely, extraordinarily important. Donna LaLonde Maybe we should wrap up by coming back to Ruby, and what you described as one of your first experiences. And that is this-to tell folks how they might get involved in a SIBS program, because that acronym might not be familiar. I'm not even sure I know what all the letters stand for. I know what the experience is, but... Lara Harmon: I don't, but I'm a layperson so I'm used to that. Ruby Bayliss: Yeah, sure, I can expand on that. So SIBS stands for Summer Institute in BiostatisticS, and essentially this program was designed for undergraduates, and also recent graduates, to expose them to biostatistics. And so there's different programs at different sites, and each of the different sites have different focuses. I would say what was really great about Emory University was that it was literally right next to the CDC, and so we got to go on field trips to the CDC. and so that was really cool to see what kind of careers you could do at the CDC. And so there were lots of different activities, there was field trips there were panel discussions, there were-we actually learned like R and SAS, and then we also had different professors lecture to us about their research. And the faculty were so great at Emory. And they were completely open and they wanted students to really come and schedule time with them to talk about some individual questions with them, about where to go next. And so I thought that was really such an amazing experience. And so we did all that in like a six-week timeframe, and so it was just unbelievable. And I actually remember talking to one of the organizers for the SIBS program at Emory, and they were telling me about how they were considering not accepting recent grads, and I told them that I think it's important that recent grads are included. Because I was a recent grad when I went to SIBS, and and I can honestly say if I hadn't gone to SIBS, I definitely would not have met Loni at ENAR, because I wouldn't have even known about ENAR at all. And it was actually Renee Moore who connected me with Loni, and Renee Moore was sort of the head organizer of the SIBS program. And so it's a great networking opportunity, as well. And yeah, no, it was just such an invaluable experience, and every time that they send me emails asking me to talk about my experience, I'm more than happy to talk about it, and just talk about how great that program was. And the thing was for me, as well, was I went to a very small liberal arts undergraduate college, St. Catherine University in Saint Paul, Minnesota. And it was great, because the classroom sizes were small, you had a close relationship with your professors. Unfortunately, though, they didn't necessarily supply as many opportunities necessarily. [TRANSCRIPT CONTINUES IN REPLY]

[TRANSCRIPT CONTINUES] And so when I found out about SIBS, I completely went out on my own to find that opportunity. It wasn't something-it seems like SIBS is definitely becoming more well-known, but it's still not... To a lot of people, they don't even know it exists. And so it's it's just a great opportunity, and it would be great to even get more sites open and more people can attend. Because I think when I went there were only six different sites available. There weren't very many. So I'm hoping that the program can grow, because it's just such a phenomenal program. Loni Tabbs: And I just want to piggyback off of what Ruby had mentioned already about SIBS. Because it's not a program that is at every single university across the country, it is competitive, but the cost associated with even participating is covered for these students, as well. And so not only are they building these relationships and getting a strong foundation, a good chunk of these students move on into PhD programs for biostatistics. And sitting on admissions committees myself for PhD biostat programs and also masters programs, students that go through a SIBS program, they have a certain perspective that other students don't have. And so then their actual application becomes more competitive when they're going into these graduate courses. So I echo what Ruby was saying in terms of I wish there were more of these programs that are funded, and they're funded from NIH, and so hopefully it can continue to grow, so that it can increase awareness for the field. Lara Harmon: Thank you for talking about that. I know afrom my own perspective, when I went to college I did theater, but there's so much you don't know is out there that afterwards it's like, oh, I could have taken advantage of that I could know more about what I'm going to do and with stats that's so important tbecause, stats and math, it's such a an abstract field to everybody who's looking at both of those from outside. So, yeah, I'm really glad to hear that they haven't decided not to take recent grads, that's good. The earlier, the better. I work with our student chapters, and I think the more people can know... The earlier the better they can start looking for opportunities, the better it is. Donna LaLonde: Well, I think that's that. I'd say it's a perfect way to conclude a Mathematics and Statistics Awareness Month conversation to let people be aware of an opportunity. And I'll just add that you're reminding me that, Loni, we may have had the answer, but we can make our answer better by completely describing thes opportunities on the education website of the ASA. So note to self on that, that we should add that to the student section. And of course REUs [Research Experiences for Undergraduates] funded by NSF, which is a bit different experience, but also speaks to your networking and getting involved. So thank you very much! [END TRANSCRIPT]

[TRANSCRIPT CONTINUES] Lara Harmon: I've talked to a lot of folks who are like, communications is really important and we have to follow up and work on that. But that's really interesting. And piano would be a good. And this is a nice segue. So we've established that math classes are extremely important but that piano is also a possible thing, so what do you like to do when you're not working or researching or teaching? Eric Laber: I like to play squash. So that's something I started playing a couple years ago. I highly recommend you play squash, kids! If there's anything you take away from this, it's that you should go play squash. I started playing it a couple years ago and I had never even seen it before. So now I'm totally obsessed. So I do try to play squash when I can, and my dog and I compete in agility, so that's another thing. I got into that when I moved to North Carolina and I was trying to do North Carolina things. So that's something that I've enjoyed and didn't know about until I got here, either. So those are my two. And then I read a lot, so… I read a lot of all sorts of things, sci-fi and nonfiction. Donna LaLonde: So in fair disclosure I've asked this question before, but for the dog lovers out there I have to ask: What's your dog's name and what type of dog is it? Lara Harmon: [laughs] I knew you’d ask about the dog. Eric Laber: His name is Merlin, and he is a mutt, so a mixed dog. And I was trying to see if I had a picture of him in here but… Oh, yeah, here we go. This is a picture of him when he was in the lab. He's sleeping on our bench. Looks a little poodle-y in that picture. So he does come into the lab sometimes and hang out and gets lots of attention. So he likes that. Lara Harmon: So it's squash and agility training. It's a good combination. Okay, so we have the last pre-planned one. So this one leaves it in your court, kind of. What question didn't we ask that you'd like to answer? Eric Laber: I think you didn't ask what advice I would give to a 15-year-old self or just… I think maybe the advice I would like to give to students who are you now starting their undergrad or thinking about starting their undergrad and eventually going to graduate school is to really focus on seeing how good you can become at something. So I think that college and graduate school are a really rare opportunity for you to try to become as good as you possibly can at something. So whether that's math or statistics, which I hope it is, but if it's something else, just see if you can find your own edges and push yourself. Because the obligations of life will eventually sort of consume your time, and so you can really focus on self-improvement during those times and you can find out what you're made of. And I think you can find passion in whatever you pursue as long as you really try to become the best you possibly can. So for me that was statistics and math, but it could be anything. But, I think, don't miss that, because you really won't have another chance, I don't think, in your life, so make the most of it That enough? Is that too generic of advice? Lara Harmon: No, no, not at all. Donna LaLonde: That’s great advice, yeah. So any advice, Eric, on how to begin to do that? It sounds like you knew-although you said in high school, you were the meticulous C student, but how did you know it was math? Or how did you find that that's the edge you wanted to push toward? Eric Laber: Well, I started out as a triple major. I was physics, math, and philosophy. Because I have this problem where I kind of like everything. And then I decided that just in spending time thinking about those three things that I really did want to do math because it felt like it was underneath the surface of all three of those subjects some way, although maybe philosophers would disagree with me. And so then it turned out to be the thing I wanted to learn more about the most and so I decided to really invest my time there. Donna LaLonde: Very cool. Lara Harmon: That is a great and terrible problem to have, being interested in everything. [TRANSCRIPT CONTINUES IN REPLY]

[TRANSCRIPT CONTINUES] Donna LaLonde: Yeah, no, I think it’s wonderful. We have a collection of folks who are interested in everything. What made you switch to UCLA? Any advice on small college versus large school for undergrad? Eric Laber: Yes. So there were two reasons. As I became more interested in math, I kind of exhausted all the math classes that were available at the small school I was at, but also at the time I was-so I guess there’s three reasons. At the time I was a professional magician and LA was a much better place to do that than rural Wisconsin. And I also was a bit sick of the cold. So I grew up in Minnesota, and walking through the snow and the slush, I thought my ancestors should have chosen better where they were going to live. And so I wanted to go and get out of town. So those are the main reasons. Donna LaLonde: Fair enough. Lara Harmon: Alright. Donna, do you have any more questions that we should follow up with? Donna LaLonde: I appreciate very much the insights that Eric’s shared with us, but I'm guessing that there are other entries in that journal that we should let him get on to. Lara Harmon: Yeah, probably so. But, yeah, thank you a great deal. This has gone really well. Thank you very much. [END TRANSCRIPT]

[TRANSCRIPT CONTINUES] Stephanie Kovalchik (cont.): And so it's really kind of a 50/50 partnership, and as part of that the members of GIG, as we call it, they have sort of a joint role. So we both have responsibilities with industry and then our responsibilities with Victoria University which are sort of a traditional academic role. So as far as teaching, I do coursework. Usually more guest lectures. There currently isn't an entire course that I run myself, so I will do that. And then I have a number of full day or weekend type of workshops that I’ll usually do usually a few times a year that focus on statistical modeling and prediction in in sport. Donna LaLonde: That's wonderful. So you mentioned that statistics actually came in graduate school, so maybe the answer to this question is statistics, but is there a class or classes that you didn't take in college that you wish you had? Stephanie Kovalchik Yeah, I mean, there's so many things, right? Donna LaLonde: Top choices. Stephanie Kovalchik: I know. I guess something that's immediately in my primary field, stats, that I think I wish I had started earlier and I could see really being important to the work that I do day-to-day right now would be spatial statistics, actually. Because I never had a formal course on spatial stats, but it is something that's really important in sport right now because we're getting a lot of tracking data, the richest juiciest datasets that people are working with at the moment, and they always have a spatial and temporal component, which is like the characteristic of those. So I think that would be something that I think would have been a big help, to have gotten some earlier background with that, I think. Another area as well is with those data, they require usually a lot of pre-processing and it effectively comes down to some signal processing methods where you have to filter-smooth these data, and I think that would have been something, as well, to have a bit more background in. So I think that's probably the most immediate. And then other things in terms of just being a good team member or a manager supervisor that we don't really get much formal instruction on, those. And so I find that I am now and then doing a lot of reading on project management, and in our group we've come around to the sort of, like, agile project management. We've taken a bit more of like a startup philosophy for how we maintain our projects because we do a lot of product development in addition to traditional academic activities like paper writing, and that whole area of managing projects and setting clear objectives, that was all kind of new. so I think it might have been interesting to see what instructors in that area say would be good practices there. So I think that would be interesting as well to have gotten a bit of formal study with. Donna LaLonde: That’s great. So you've kind of talked a little about this, but if you had to pick the coolest thing about your work or research, what would you highlight? Stephanie Kovalchik: Yeah. You think in sport it would be, you know, ‘oh, I get to talk with players’ or something like that, but actually it's honestly when I think about the moments when I get most excited, it's really that point when you have a challenging problem and it's not that obvious what the answer is. And then you have that lightbulb moment where you can see all of the figures and tables coming together of like, oh, how exactly this study would go. I love that. I guess it comes down to the model building stage. And that part of a project is really the most fun to me, where you've done a bit of exploration with the data and now you're starting to kind of understand maybe this measure or outcome that you're interested in, and fitting a model to try to describe that in a mathematical way. That to me is like the most exciting and part of what makes it exciting, though, is to also be able to connect it directly to some way that it's going to have importance for the sport. And that just kind of comes because we always look at questions that we think are relevant to understand something about tennis performance. And so in the background there's always that awareness that, ‘oh, if I can solve this, I know that it's likely to have some positive impacts back to the sport.’ So I think all of those things together make those moments particularly exciting. Donna LaLonde: So, is it still tennis that you like to do when you're not working on research? Lara Harmon (ASA Marketing and Online Community Coordinator): That's a good question. Stephanie Kovalchik: I do like to play socially, but it's just purely for fun. But I do like to be on the court, so I usually once a week will do social doubles, which is a lot of fun and it's very humbling. But it's good, yeah, definitely being active. I love just the outdoors and walking my dog or hiking and things like that, so I've always been a bit of a jock in that respect and still try to get in some activity. I also do quite a bit of dance actually and I like that combination of movement and music. And it feels a bit more of an artistic outlet that sometimes it doesn't always feel like I get a chance for in my day-to-day work. But I actually think that spending that kind of time outside, it's a very specific type of work that can actually help me feel sort of more creative. Because there's a lot of creativity, I think, with the work that we do in stats. Like when you're having to solve problems that maybe nobody's ever thought about or you haven’t heard of people talking about. And I think building models or designing R packages and things, those are quite creative things, even though they might not fit into the traditional sort of acts of creation that we think of. Donna LaLonde: Do you perform for dance or…? Stephanie Kovalchik: Yeah, I have, I have occasionally. Like I'll do teams where we'll do group performances and another routine and then you just all very locally--it's nice to have a very specific goal where it's, there's this performance date that we've all committed to and working together to be ready when that comes around. And I think, yeah, it's a good way to experience it. But I also just enjoy group classes where it's just for fitness, but being with other people that are enjoying the dance and the movement all together… I think it's one of the best ways to experience it, yeah. Lara Harmon: It sounds like a good mix. It's always important to explore all sides of things. [TRANSCRIPT CONTINUES IN REPLY BELOW]

[TRANSCRIPT CONTINUES] Donna LaLonde: So my last formal question is what question didn't I ask that you would like to answer? Stephanie Kovalchik: Oh, that I would like to answer. In terms of thinking of careers, the thing when I think back about what was the key to the direction that I took now… I think it was really just really listening to what your passions were telling you was a good fit for you. And it's one of those intangible things, but I think it's often we think about things like the degrees, the papers, like these very observable things as the goals to go after when judging what makes a great career. But I think that can lose sight of your day-to-day experiences or actual process, and I think it's how you enjoy the process of what you do and what keeps you excited day-to-day that is really going to make a difference for what you yourself feel has been a good choice as a career. So I think that was something I didn't realize as a student for example, but luckily when that time came and I learned about this opportunity to do work in in sport, even though it's an area that very few people can actually get a formal degree in still… And I think in a way, at the time, one of my worries was that, oh, my advisor from graduate school, he might be really disappointed because they’ll all think I've just gone completely a weird direction with all of this training that they did with me. But I think it ultimately came back to thinking, well, this is where I spent all of my time thinking, so that has to mean something. And so just listening to that voice even if it didn't fit in with what might be the role others envisioned for you or you thought of for yourself. So I think that's been something that, thinking back about the big milestones and turning points, that that was a really critical one. Donna LaLonde: That’s great advice, especially for the younger folks who might be listening to this and trying to figure out what their passion is. To know that they should listen to their heart. Lara Harmon: As early on as possible. Donna LaLonde: Well, thank you so much for your time. Unless Lara has questions? Lara Harmon: I think from what you've said, you've kind of covered the biggest question I would have had, which is given the choices you've made in your career, what helps take those big risks? Because like you just said, you took some risks and I'm sure that took thinking and getting right over that edge somehow, jumping for it. So what advice would you give students if they're thinking about something and can't decide whether to go for it or not? Stephanie Kovalchik: Yeah, that's a great way of putting it. And it's interesting as well, to think at the time, the biggest risk was changing essentially my field, going from traditional biostats into sport, making that jump. And at the time I don't even think I was really that aware of the risk. I mean initially I think it was clear, almost, to me that there was really only one choice, which was to definitely move into sport. Just because I had already at that point spent several years where it was just an all-consuming thing this, at the time, I guess people would call it a hobby, because it was something that I did outside of work. But really in terms of where I was spending my time thinking about and what I was really most interested in, it was obvious from that point of view. But I think it was important to have the confidence that I knew what that role would be like. Like what my days would be like and I could sit down and say that these were all of the research questions that I would want to tackle in the first year. So I think that was important, is that what I would be doing was quite clear in my mind. Also being confident that I had the abilities, I had the skills, at that point that I could do those things and pursue them, or for the things that weren't maybe as clear to me exactly how it would work out that I was still confident that I could learn what I needed to to get there. So I think that was important, that I didn't jump in having never really done anything in that area. I felt like I did already have a body of work and time and experience and that even though it had been done fairly independent of my primary work. So I think in a way it made it seem less of a risky endeavor, and I felt that having that background and interest that it really just came down to where I thought I was going to have the most impact. So thinking ahead and it's, like, in five years if I stayed where I was what did I think I would be versus in five years if I took this role what could I be doing? And I think when I had that kind of hypothetical scenario with myself that it was really clear that for me. It was important that if I was going to take a risk in making this move that I would be able to be in a situation where I could help to have some real impact or a big idea. I always put it in terms of if I do anything in my career, I would like to have like at least one great idea. Maybe years from now people look back and say, oh, she did that. I thought that would always be a wonderful thing to be able to have done. And I thought I was really only going to be able to do that if I did take this this change. And so at that point it was sort of a no-brainer for me. Lara Harmon: Thank you! Yeah, I really love that answer. You've gone to such depths to explain things and to be so honest about your career path. That's really wonderful. I think our students will love it. Donna LaLonde: Yeah, absolutely. We are so excited that you were able to participate. Thank you so much for getting up very early. Lara Harmon: Yes! Stephanie Kovalchik: I definitely hope that, yeah, having this experience, that other students who might be thinking about maybe unconventional areas where they can do math and stats or even sport itself, that gives them a better idea. [END TRANSCRIPT]