Sara Stoudt is an applied statistician at Bucknell University with research interests in ecology and the communication of statistics. Follow her on Twitter (@sastoudt) and check out her recent book with Deborah Nolan, Communicating with Data: The Art of Writing for Data Science.
Episode Description
Communicating clearly about data can be difficult but it’s also crucial if you want audiences to understand your work. Whether it’s through writing or speaking telling a compelling story about data can make it less abstract. That’s the focus of this episode of Stats+Stories with guest Sara Stoudt.
+Full Transcript
Rosemary Pennington
Communicating clearly about data can be difficult. But it's also crucial if you want audiences to understand your work. Whether it's through writing or speaking, telling a compelling story about data can make it less abstract. Communicating with data is the focus of this episode of Stats and Stories, where we explore the statistics behind the stories and the stories behind the statistics. I'm Rosemary Pennington. Stats and Stories is a production of Miami University's departments of Statistics and Media, Journalism and Film as well as the American Statistical Association. Joining me as always is regular panelist, John Bailer, emeritus professor of statistics at Miami University. Our guest today is Sara Stoudt. Stoudt is an Applied Statistician and Assistant Professor of Mathematics at Bucknell University with research interest in ecology, and the communication of statistics. She's the author with Deborah Nolan of the book, Communicating With Data, the Art of Writing for Data Science. Sara, thank you so much for joining us today.
Sara Stoudt
Yeah, no problem. Thanks for having me.
Rosemary Pennington
You have been doing a lot of work around data communication, about writing about data, why did communicating data become this passion of yours?
Sara Stoudt
Yeah, it started sort of serendipitously, in that Deb Nolan, when I was in grad school, was thinking about teaching this class for undergrads, and reached out to me about maybe helping out. And so at that point, I hadn't really thought of myself, maybe as a writer, like, how do I claim that title, but through working on that class, and then writing the book after that we sort of both had to grapple with like, yes, we're statisticians. But we do a lot of communicating. And at some point, we have to claim that sort of title of writer as well. And so I think by starting with that process, and really working through the book, maybe sort of get more into it and think about how I might apply it to my teaching more and how I might apply it to my own work and sort of snowballed from there.
John Bailer
So now, I gotta ask you, are you a better writer now?
Sara Stoudt
Maybe I think I'm a better writer now. I think that I think more about my writing now than maybe I did before. I don't know if that helps or hurts, but I think that I pay more attention to it. And when I'm doing other things, I'm thinking more about reading, like when I'm reading just for fun. Now, I'm like, in my head about that a little bit. And I think that's a good thing.
John Bailer
No, I agree completely, just this, I really love seeing the diversity of different types of ways that you approach ideas in writing, you know, ranging from Significance article reading to writing to another Significance piece, can TV make you a better stats communicator? So I'd like to just sort of explore those maybe in reverse order. Because I think though, the one about the TV shorts, you know, these sort of small episodes as being this model, can you give a reason why you are inspired to connect to what was going on in these small, episodic television shows? And what that might teach us about writing?
Sara Stoudt
Yeah, I think for me, I was writing a lot of talks. And I was thinking about, like, zooming out, like, how am I writing this talk, because you give a talk for lots of different audiences. And the job talk is maybe a little bit more formal. But more recently, I've been doing more talks for broader audiences. And I had to mix up my approach. And I think it's also just the 20 Minute versus like, the 40 Minute versus like, the five minute talk, like all those things, take different structures. And I was trying to think about that. But at the same time, it was like right after deep pandemic, and I had just watched a lot of TV, frankly, and rewatching, a lot of my old favorite shows, but from the beginning, and really paying attention to the pilot of like, how much has to actually get done in the pilot to set things up. And you don't appreciate it until you know what the story actually is to like, how much effort went into that? So I was thinking all about that. And I was thinking, Oh, this is sort of related to how you do the talk, like, you know, the whole storyline. How do you set it up, you only have so many minutes to get the point across. And so part of it was like me justifying watching so much TV. Another part of it was just like, how do you write a good talk? I think it's sort of elusive. And doing it for different audiences, different time points, like having a good sort of structure, I think can go a long way. And that was sort of the motivation for that piece.
Rosemary Pennington
As you've been doing this work on sort of communicating data broadly, have you noticed things that are particular hiccups for you and how have you sort of worked around them?
Sara Stoudt
That's a great question. Yes, I have many hiccups. I think that sometimes, and you might see it today, like I can tend to monologue and in my head, I'm like, yes, this all is gelling. But because I have all of this extra context, I forget that the connections are not necessarily being made by the audience. Right? It's sort of like the stream of consciousness makes sense for me, but not for everyone. And I think that gets back to the planning. And I think a lot of the work I've done recently is the planning of writing. Because you have to take that step back. And I think we can just sort of forget to do that, because we're pressed for time we're reading that talk on a plane, you know, you just don't have that sort of zoom out, like, “what am I saying” moment? So I think that gets, like planning the talk. The reading too, right? Just slowing down, I think, is my biggest hiccup. I'm sort of like, Oh, I gotta do this, I gotta do this. But if I take the time to breathe, and zoom out, like, what am I saying? What is the goal? What's the best way to do this, even starting with pictures? Sometimes I just start the talks with like, all of the plots, or the little doodles that tell the story. I think that has helped me a lot too, because I think I can just sort of jump in too quickly, and then get in the weeds. So I've been trying to pull myself out of that.
John Bailer
Yeah, that's, I recognize that same temptation. And, you know, when I've done this kind of writing, I think a lot about having to pull out, you know, in sort of thinking big picture. And one thing that really struck me when I was reading one of your pieces on or reviewing some of your slides from this storyboarding talk that you did, as part of this idea process, the process of writing is that the punch line has been organized in the form of narrative. And one of the things this podcast has taught me is a lot more about thinking about the narrative that goes along with an analysis or with any kind of work that you're doing in research. So can you talk a little bit about the kind of insights that you've kind of gained about structure from the idea of storyboarding?
Sara Stoudt
Yeah, I think the main thing is that when we do statistical work, we're so proud of all the stuff we did, we're like, I did this, I did this. And II did this fancy thing. But ultimately, that's not what the reader cares about, they want to know what you found. So I think it's this temptation of like, you want to show what you did. But that's only ancillary to what you actually are trying to say, which is the findings. And so trying to this gets back at the like, taking a breath. It's like you have to switch gears from doing the stuff to saying: What is the big picture? And so I think the storyboarding helps you sort of shift gears. It's like, don't talk about what plots you made, what analysis you did, what are the common themes? What did you find? How does this connect towards a bigger picture, and it also makes you sort of Kill Your Darlings, you can't put every plot in a paper or a talk. And so you have all these things, and you have to sort of whittle it down. So I think the storyboarding is both just like it's iterative. It's really tactile, you sort of have to think there's like, no numbers involved. It's like, maybe there's some plots, and you're rearranging, so I think it sort of helps you sort of shift that gear. And I do this all the time. I mean, to write a talk and write a paper now, I'm like a very tactile writer. And so I think doing that activity with students has really helped us all sort of shift gears, right, fewer reports have like, I made a histogram of this, I ran a regression and more just like, this is skewed left, which means this and the regression tells me this, I think helping us to get towards that sort of language is what motivated the storyboard and why I keep sort of using it.
Rosemary Pennington
When I was in my past life, when I was a journalist, I did Science and Medical reporting, sort of towards the end of my time. And I loved it. I absolutely loved it. But it was always a little tough to sometimes get scientists to talk to me, because they were always so scared that their work would be misconstrued. Or they were concerned, I had more than one say, I don't have it, like, you know, five minutes is not enough time to communicate, whatever it is, and I guess what advice would you have for, you know, statisticians or scientists or anyone who has data that they want to communicate around the fear that they're not going to have enough time to tell it clearly? Or if they or if they tell it, they're not going to do their work justice, if they sort of have to sort of make it very simple, or turn it into a narrative?
Sara Stoudt
Yeah, I definitely feel that tension. Statisticians are so annoying, because yeah. Did you say that Sara just reinforced her belief? I think it comes down to the level of detail. It's like, maybe we don't want to talk about that one regression result in five minutes because there's nuance but that regression result means something in context and you want people to know about that thing. So not to sound like a broken record, but I think it comes down to the zoom in and out thing like, I think you can zoom out in five minutes, what's the impact of your work? Let's not try to explain necessarily the details of how you got there in that sort of form of communication, perhaps. But I think it's hard because that's not the part we get the most practice with. We're in the weeds most of the time. And so trying to navigate that is, is challenging. But I feel that tension too. Like, sometimes I'm like, Oh, I don't really want to explain what I'm doing right here until it's perfect. But, but that, how are you going to get your work out there? So it's a balance, but maybe focusing on the impact first. And trying to get away from the things you feel most worried about the precision for?
John Bailer
You know, what you just said, really, really resonates. This idea is what do you spend most of your time doing? What is the focus of your effort, and one of our former colleagues, Richard Campbell, was fond of saying that people are the best writers they'll ever be when they're just getting out of composition after their first year at the University, because they don't write a lot more after that. And in you know, the ideas that you have to you become a better writer by writing, you know, that and having some structure, I think, really kind of catalyzes that in a real, real great way. So I find that this challenge is trying to help get people out of the kind of full in technical focus, and then expanding it to think about okay, now, how do you take from the technical out to the broader community? So what are things that you've been doing to kind of help the students that you work with and the communities that you interact with to do that?
Sara Stoudt
Yeah, I think one thing is just the fact that if you think about the structure of a typical assignment, it's like you do a final project, you turn it in, and then that's it. Right? You don't get the chance to iterate. And that's where you start to get at the like, what is this really saying? And so what we've done at Bucknell is sort of add in the iterative process more in the project. So we actually teach a writing intensive designated intro stat. And that means that that comes along with having to do revision throughout the semester, and they get tons of feedback from peers from the instructor. And they rewrite different parts that come together as a full report. And so they'd just like to spend more time noodling on it for lack of a better word. And so I do think we still need to push more on zooming out, what's the big picture? Because I think we spent a lot of time on the preciseness of how they're talking about the results. What does that significance level mean? That kind of thing, and that kind of class. But I think just building in time to revise before the final deadline goes a long way. I think it's hard because it does take a lot of feedback time in the semester, which is challenging to do quickly, especially at scale. But I think you have to show students that revision is part of the process. And to do that, they have to revise the final project. And so that means pushing back deadlines so that you have time for that. But the context part is important too. And I think I actually want to do more with that, because I think I'm not doing a great job of pulling that out. I feel that tension. It's something like interest at work content seems king, but thinking about how to do that, as they keep progressing as statisticians thinking more about those conclusion sections and trying to work shop those more than the results sections, which is what we ended up having to focus on at least in that class.
Rosemary Pennington
You're listening to Stats and Stories. And today we're talking with Bucknell University Sara Stoudt about communicating with data. Sara, so I'm going to sort of take this question slightly sideways, I asked a former journalism professor, revise Yes. Like we revise those kids revise till the end of the semester. But I wonder what advice you would have for a working journalist who maybe is trying to report on data. You know, most of us are generalists. Many of us are not comfortable with numbers and stats. I mean, that is a stereotype that doesn't linger, because it's sort of, there's some truth in it. So I wonder, you know, we want to communicate this clearly. Because we think it's important to our audiences. What advice given sort of what you've been doing, would you have for journalists when it comes to reporting on stories that involve data, whether it's complicated or not?
Sara Stoudt
I think one thing is like, have a buddy, like, statisticians we're friendly. If you find someone that you'd like, work well with workshopping it that way, because I have collaborators who just help me write better in general. And I think journalists can have that too. And I would love to see more cross pollination with that. Because, yeah, like statisticians want to be able to write for broader audiences better, too. So that seems like a win-win. I think there's some common statistical things that everybody is fussy about, and doing a little reading up on that. I mean, you have a lot of, I'm not saying do more work, because I know, journalists are busy and doing important things. But maybe like, you know, a little community that talks about some of those big ticket items, like, you know, how to report on a p-value, how to report on a confidence interval. It's dry, but that's the stuff that gets you, but maybe doing it in a more community setting. And maybe I started getting a group of statisticians and journalists together to do that. Because as teachers, we face that, too. It's like, how many ways can I explain this? It's still confusing. So it's good for us all to practice, I think. But I don't have any magic solutions. You never know, I guess.
John Bailer
Yeah. So, before we started the podcast, I team-taught a class with a journalist with Richard Campbell, this was quite a while ago, and it was interesting to me to think about the style of writing was so different, that he was talking about then what I was, was thinking about, and that I had done professionally. You know, he was there, there was a sharpness and focus to what he would bring to writing that I found myself being surprised by I mean, not not in a bad way. But just, it was just such a different style. And I was realizing there were these multiple epiphanies for me about kind of this idea of how often in my own writing, I wasn't getting to the point as quickly as I could have. And I wasn't kind of spending so much time on the talking about process, but maybe not getting to the punch line with this the kind of emphasis that it really deserved. So that so I, I mean, I think that the exposure that that for me, as a statistician, and working with with journalism colleagues, has helped me become a much better writer, and a communicator, because of trying to think about, well, gosh, if I tried to do what they're doing, how does that what does that mean in terms of how I produce a product had I written or oral product? So it sounds like you've learned a lot and went through these processes, but also these examples that you found whether it was from pilots from a television show, or from other models? I know that you're sort of thinking that a question will eventually emerge. And I'm wondering, yes, I always wonder, and that's always the problem here. So I would like though, to get to get back to this idea of the pacing and timing of a story as it as a sort of parallels, you know, a big bang theory episode, you know, so I love this idea of the these parent thinking of these parallels between early on introducing kinds of characters and introducing context, and then kind of introducing some conflict and some resolution to conflict and some punch line to the very end. So could you just kind of give us a little kind of a talk through of kind of, of the parallels between kind of, you know, starting out where, where the characters meet? And what does that mean in terms of statistics, and then going through the rest, please?
Sara Stoudt
Yeah, so if you're giving a talk about your own work, you know, everything, but literally, people don't come in with any context. And they have to like to care about it by the end of your talk, because you want them to follow up, because you're not going to tell them everything. Same with the pilot, it's like you have this like 20 minute period, to hook them and have them come back. And you have to set up everything. They don't know anything about the characters or the setting, like, what's the show gonna be about. So you have to cover a lot of ground. And if you think about how you want to present your work, people have to understand why you're doing the work, because that's part of the way of getting them there. Why is your work hard? Like, why is it a big deal that you're doing the work and sort of connecting it to what other people might be doing. So it's sort of like, actually, in the first talk that people hear from you. It doesn't even matter how you're doing the thing. They just need to know why you're doing the thing. And what makes it interesting, or hard that it's worth doing, because they'll follow up and read the paper after that if they care. Same with the pilot, they'll keep watching the show once they're sort of brought in. So I think you have to think about it in terms of stripping it way back to when you started the project, right? Like, why? Why did you pick it as an interesting problem? Who brought you the context, if you're a statistician who's working in applied field, you also have the challenge of talking about the context of the work so like I work in ecology, if I'm presenting at a SAS conference, there's some baseline ecology, I also have to cover in that talk. Right so you can imagine like, okay, maybe ecology terms are like the characters, you got to learn what they're about. You have to learn what the major conflict is. There's an ecological conflict, like why do I care from that point of view? But then there's a statistical conflict of like, why is this a stats problem? That's hard and I started going from there. But I've described all that, then do you have, like, 20 minutes?
John Bailer
No, that helps a lot. I mean, the idea of the the images ties back to kind of some of your storyboarding, I love the idea of thinking about putting all of your plots on, you know, on some display and sort of moving them around, and maybe connecting them in terms of the story that you want to tell annexing out the ones that aren't effective. When I taught visualization or other kinds of data practicum classes, I would often say you'll make more than 10 times more the number of figures you'll ever include in a report that you issue, just because you're trying to find the right way to tell the story. And ultimately, for me, I often found that if I could generate the figure that spoke to me, I could write the text that would describe it to others. So do you find any kind of relevance and importance of kind for you doing the visualizations as part of input and inspiration for the text that you would produce?
Sara Stoudt
Yeah. And actually, I've been doing a lot of things, not even on the computer, but like, sketching what is the graph I want? That will show me what I need? Or what do I expect this to look like if what I'm thinking about is true. And then trying to make that graph. Because I think sometimes when I'm just making graphs on the fly, I'm making ones that are easy for me to code, but are not necessarily the right graphs. And so I've been doing a lot of that sort of thing, like doodling. And I think that has helped and especially if you're thinking about the right conceptual diagram for explaining your work, that is also something that I need to draw first, because I'm not great at the like, shapes on the Google Slides or whatever. But I think that it really helped me solidify the story. Because sometimes if I'm just looking at a bunch of, you know, scatter plots, histograms, it's hard to, like, really see what's going on. So thinking about the maybe less traditional visualization that would like to really consolidate everything, and then trying to think about like, is this a plot I can actually make?
Rosemary Pennington
So you've been doing this work for a while now you've done work around how to present and the storyboarding and you have the book, what sort of next for you when it comes to stats communication, like what do you want to be working on next?
Sara Stoudt
Yeah, I think for me, personally I'm thinking a lot of like creative writing that's related to stats and data. So thinking about either data or statistics concepts as constraints for something like maybe like, Could you write a poem that's constrained in a way that's informed by data? Or could you write short stories or speculative fiction that have these sort of like data II concepts? You think there's all this sci fi now, that has to do with, you know, climate change, or the rise of machine learning and like the ethics of those things? I think that we could also write more stats focused fiction, not just for the sake of writing them, but I could see them being useful teaching tools. I think I'm personally just trying to break this sort of false binary of like, you're a quantitative person, or you're like a creative type. And so I'm really interested in trying to fuse those and like, can we do more artsy things with data? So that's what I'm thinking a lot about. I don't know if that's necessarily going to end up my professional take on communication. But I'm really trying to do that for myself. I think when I started down this road again, I didn't really claim the ownership of the title writer. And now that I feel like I can say that, I feel like the next hurdle is like, Are you a creative writer? Like, can I write more than just nonfiction? So we'll see where that goes.
Rosemary Pennington
Well,thank you so much for being here today, Sara. That's all the time we have for this episode. It's been great talking with you.
Sara Stoudt
Yeah, thanks for having me again.
Rosemary Pennington
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.