Latoya Jennings-Lopez hosts this special episode of Stats+Stories with the children of Howard W. Bishop middle school. Listen to Alyana and Collin ask our host John Bailer and other special guest Wendy Martinez about their careers in Statistics, and how young people can get involved early. From topics such as job prospects to COVID-19’s impact, listen to what kids curious in numbers want to know.
+ Full Transcript
LaToya Jennings-Lopez: Good morning. I am LaToya Jennings-Lopez and I’m joining you this morning with Stats and Stories. Stats and Stories is a production of Miami University Department of Statistics and Media, Journalism and Film as well as an American Statistical Association. Joining me are our regular panelist John Bailer, chair of Miami Statistics Department and Wendy Martinez, the President of the American Statistic Association, and also the Director of the Math Statistics Research Center and also the Director of the Math Statistic Research Center at the Bureau of Labor Statistics. Also joining me is Alyana Palmer who is an eighth-grader at Howard Bishop Middle School in Gainesville Florida and Collin Dunmore who is a seventh-grader at Collin Dunmore who is a seventh-grader at Howard Bishop Middle School in Gainesville Florida. How are you guys doing this morning?
Alyana Palmer: Good.
Collin Dunmore: Good.
John Bailer: Just wonderful.
Wendy Martinez: I’m doing very well, thank you. I’m talking to you from my basement.
Jennings-Lopez: Making sure everybody is staying safe, correct?
Bailer: That’s right.
Dunmore: Yes ma’am.
Jennings-Lopez: I’m really excited about the show today because we get to talk about statistics and data, and so two of our panelists this morning, the students at Howard Bishop Middle School have also been excited because they been learning about data and statistics through their after school program. So, let’s start with you guys, Collin let me ask you how does data- how do you connect data to your everyday life?
Dunmore: Well, I’m connected with the school and my grades and all those other things. With the test, the average amount and then that’s your overall grade and also data.
Jennings-Lopez: Okay good. And Alyana, how do you connect data to your everyday practice?
Palmer: Like, I guess like when I’m picking out clothes to wear or like stuff to eat.
Jennings-Lopez: Okay. So, when you talk about your favorite restaurant, like how do you know that’s your favorite restaurant? Because you compared it to what?
Palmer: Other restaurants that I go to.
Jennings-Lopez: Right, so that’s another way. So, I know we talked about that and I know we- in our conversation that we had about data and how to use data you guys had some questions as well. So, at this time we’ll start with you Collin and you can just talk to the panel about some of the questions you had about how data is important and how you can use data, especially being in middle school.
Dunmore: Mr. John?
Bailer: Yes sir.
Dunmore: How do you guys find the data of different races when it comes to the Coronavirus? Like how did you know that there was a certain amount of black people or a certain amount of Caucasian people or any race have more Corona or less Corona than all the other races?
Bailer: Wow, that’s a really important question, Collin. I mean, I think that any time you’re going to study disease and study things like racial/ethnic disparity and disease you have to make sure that you’re very careful in how you collect the information, and then how you track it. You know, you're starting with probably a life-changing unprecedented event. All of us are living through something we’ve never seen before and we’re not even sure how we’re going to be- how it’s going to play out. So, I guess you’re asking about some of the disparities that have been seen in terms of the fatality rates, you know, how many people are dying given the disease, so what are the- so I’m not an expert in this by any stretch. I’ve looked at some of the data and some of the summaries which are suggesting that there’s some racial disparity in terms of these fatality rates. I think part of it is just to make sure that you look very carefully, and you record the kind of data about who’s getting it, how they’re getting it, what’s the context in which they’re getting these things. And so I think that to be able to understand this is- at one level the description is to say what’s the data look like and make sure you measure it carefully, and then once you’ve done that, what are some of the causes that might explain what’s being observed. Does that respond?
Dunmore: Yes sir, a little bit.
Bailer: Wendy, do you want to join in? So, Wendy, he started with a really hard question for me. I don’t think this is fair Collin, I think you’re just picking on me.
Martinez: I can’t tell you how happy I am that he asked you that question.
Bailer: Man. I’m just thinking oh, I was waiting for that softball question and he starts with one really hard.
Martinez: I know. [Laughter] So, you know I guess I think that one of the problems with trying to deal with something like the Covid-19 is that we’re right in the midst of the crisis and it’s really hard to think about what types of variables we should be measuring, or characteristics like the demographic characteristics like race, and you know other, I don’t know, maybe income and self-worth, and so I think it’s- and I guess I imagine that the health care providers are so busy just trying to save lives that, you know, they don’t think about these things, so I guess we’ll have to see later after it’s done, or I guess kind of slows down a little bit. And hopefully, we’ll have the right data information so we could answer some of those questions. But I think it’s pretty difficult to do it while everything is going on. But it is really important because you know, we need to make sure that everybody is taken care of. But that’s a really good question.
Dunmore: Okay.
Jennings-Lopez: Okay so just to kind of reiterate what John said, when you do look at the data though, you know how we look at who- what was the things you named, you said you normally look at the who and the how and what, those variables? Okay.
Martinez: And I think I mean there are different ways to do a- like you could do a conduct an experiment, and chime in John whenever you want, but you know sometimes you’re just observing what’s happening but I think it’s always good to collect as much data as you can because often times when you get done and you’re looking at the data there's oh, I should have collected ‘x’ because that would really you know help me answer the questions that I want. Sometimes we don’t know the questions before we collect the data, which is probably what’s happening with COVID, right John?
Bailer: Well yeah, and so, have you guys studied taking samples in your classes? So, Collin, Alyana, is that something that you guys have studied? Have you talked about that?
Jennings-Lopez: Yeah, in Science you did the studies where you got into those groups and you had to make the subgroup take the samples of each group.
Dunmore: Oh yeah.
Bailer: Okay so that’s a really interesting challenge right now with COVID because people are saying well, what percentage of the population is positive? And we’ve not done any- we’re not taking a sample from the population yet and testing that sample. There are some colleagues of ours that have called for that, that that’s something that we really need to do if we really want to understand how common this is we need to understand that. So part of this is- I mean this is something that Wendy’s shop does a lot of is doing these very important kinds of design surveys where they're very careful about how they define a population and how they take information, how they sample from that population, and then ultimately making conclusions from it and that’s something that I think is still being done right now with this pandemic.
Jennings-Lopez: Really good. Good stuff good stuff. Thank you, John and Wendy. Alyana, you have a question?
Palmer: Yes ma’am. So, when I get out of high school and go to college, I want to be a traveling nurse. I was wondering what type of data would I need to compare a station nurse in a hospital or a traveling nurse?
Martinez: Okay, alright. So I guess I would like to do a little plug for the Bureau of Labor Statistics because- so, we collect data on a lot of things related to job opportunities, employment, and, in fact, the monthly unemployment report that comes out, we do that. But the reason why I'm going into all that Alyana is because the Bureau of Labor Statistics publishes something called the Occupational Outlook Handbook, and LaToya you might want to take a look at that for your students because it’s a fantastic resource. It has information about all different types of occupations you might have, and it tells you about what education requirements there are, what’s the job outlook for that, say, ten years from now, gosh, maybe what types of tasks you might expect to do- I’m trying to remember, so hopefully I’m right. But that’s a great resource whether you’re a student or even later in life and you’re looking to change your career. So, I would look at that and of course, you always want to know what wages you could expect. So, the Bureau of Labor Statistics has information on that too, about wages for different occupations. Depending on what state it is too because you might want to know, well maybe I want to move to California or something and you want to know what the job outlook is there. Okay, I guess I talked enough, go ahead John.
Bailer: Thanks, Wendy. Well so you asked about nursing and I guess in full disclosure, my wife is a nurse. So, she does a lot- so this is her world. But maybe an even more important disclosure- so Wendy did a plug for BLS and all that I’m the President of the International Statistical Institute this year, and one thing that we’re going to be doing is we’re going to be part of a number of groups that are celebrating the 200th anniversary of the birth of Florence Nightingale. Have you heard of her?
Palmer: No sir.
Bailer: Okay, so she is credited with kind of being the- with founding the first school of nursing in the world. And one of the things that she did was she used data to look at why people were dying with such high percentages in hospitals. So this is in the- you know, we’re talking in the- you know in the 1800s and during the wars that were occurring there and that the British were participating in, and it was just horrible sanitation conditions and she looked at the data comparing before and after when they started doing sanitation. So, data has been part of the practice of nursing from the start of it as a recognized profession. So, you, as a nurse, as someone who’s going to be there, you’re going to be looking at evidence-based practice. What’s the best thing that you can do in caring for patients to lead to the best outcomes for them? So regardless of what kind of practice of nursing you do, you’re going to be using data to help inform you about how to best take care of your patients.
Jennings-Lopez: Thank you.
Bailer: Sure.
Jennings-Lopez: That is uh- all right did that answer your question, Alyana?
Palmer: Yes ma’am.
Jennings-Lopez: Okay so in looking at… So, do we have any other questions Collin, do you have another question?
Dunmore: Miss Wendy, when did you know you wanted to do your job? Your profession.
Martinez: That is a really good question thank you. I've come to realize that I don’t think there's a real typical path to becoming a statistician, and in fact, some of the people I would consider to be famous statisticians came at it from- whether they were engineers or economists or physicists, different types of professions. When I was your age I guess I wanted to be an astronaut. Yeah, I wanted to be an astronaut, at various times I wanted to be an archaeologist or historian. Then I figured there probably wouldn’t be enough- you know like a really good job in being a historian, so I got into – well, I wanted to be an engineer too, but that didn’t happen. So anyway, I ended up working for the Navy- oh, interestingly enough I guess I did have a job as an engineer with the Navy, and my office mate- he was going to George Mason University and he convinced me to work in computational statistics. I’m sorry that was kind of a long answer for how I got here today, but it’s kind of a twisty path I guess, to where I am and- which I think happens to a lot of us, so there's really no right way to do things, I don’t think, and we just take the road as it leads us and we get to where we are. But I'm very happy as a statistician because it gives us a chance to work in many different areas and to do cool things with data.
Bailer: So, can I be bold enough to answer the same question? Is that okay?
Jennings-Lopez: Yeah.
Dunmore: Yes sir.
Bailer: You know, I think when I go back in time and think about when I was the age of you two, I liked math and I liked science. I don’t know that I knew what I wanted to do and I – when I went to college, I was pre-med. That’s what I was going to be and I thought that’s what I wanted to do because that’s what you did if you’re good at science because I didn’t want to be- if you’re good at math I was told you got to go into accounting, you’ve got to go into or engineering and I wasn’t sure I wanted to do either of those, so I thought oh okay I’ll do pre-med. But back when I was your age we didn’t have- we didn’t talk a lot about data and statistics. And I think that you two are getting exposed to topics much earlier than we did. So, I think that there is a generation of students starting to think about statistics as a career and as a path. Statistics or data science is often the kind of paths that people think about. For me it was when I was – I still was taking a lot of math classes because I liked it and then I finally took a regression class where you were trying to predict things, you’re trying to model input and look at the output and I thought oh this is so cool. And that was kind of when I got hooked. But you know what? It was just that I like math, I like science and I thought what’s the place where I can do both, and statistics have proven to be a great place to do it. And I get to meet really cool people like you guys, so it’s been a great job for that.
Martinez: Yeah I guess I was somewhat similar because I was really good at math in high school and so when I worked on my undergraduate degree- I did want to be an engineer but the school didn’t have an engineering program, so I did a double major in math and physics thinking that would be the closest thing. And then I did go to NASA Langley Research Center but not as an astronaut, unfortunately. And you know, I did get a degree in engineering there and then finally became a statistician.
Jennings-Lopez: That’s an interesting statement that you said earlier, John, about data wasn’t really talked about, because it wasn’t talked about when I was in middle school either, but recently like in the last five years even in my profession I'm hearing more about it. I mean we’ve already talked about data in education but like in other fields I'm noticing that they are constantly saying look at the data for this, looking for the data. So, I have a question for the group, do you guys feel like because of social media now that we’re kind of more hearing about it more than we normally would have if we didn’t have social media? Anybody on the panel can answer that question.
Martinez: I guess I think so, I mean I'm not- I don’t do too much on social media, but just the fact that people are communicating, you know, and there's this flow of information that- yeah, I think there's something to say about- I think you’re right, yeah.
Bailer: So, like a lot of professors I’ll answer the question that I want to answer, not the one you asked. [Laughter] No I’ll answer the one you asked. So, when you talk about social media I'm also thinking generally about just the use of the internet and even doing what we’re doing now, we’re recording this all remotely. The tools to be able to interact with data are so much better, and we’re generating data in different forms and in different types. So, your social media account is creating a whole path of use. You know, what you like, what you dislike, what you follow is suggesting some characteristics about you that’s information that can be understood and analyzed. The tools are so much better now. So, you know, so, Alyana and Collin have you ever used a computer?
Alyana and Collin: Yes sir.
Bailer: You know when was the first time you used a computer? How old were you when you first used a computer?
Jennings-Lopez: Maybe kindergarten.
Bailer: Kindergarten okay. How about you Wendy? When was the first time you used one?
Martinez: I would say maybe in my twenties.
Bailer: I think I might have been 19 when I saw it and it was awful. We were using cards, it was nasty. You know you’d make a mistake and you’d find out about it 45 minutes later if you were lucky. I mean it’s just; you know this was back when the- of course, this was when the earth was cooling, but [Laughter] we were- it’s just so much more fun to do this kind of stuff now. We have these tools that we can use that generate a lot of data like you were asking, but also, there are so many neat tools and opportunities to analyze these data now.
Jennings-Lopez: And that’s a good point. Now it’s fun, but back then it wasn’t. Back then it was work to use your computer and orange type of screen that made your head hurt. Now you have cool graphics like Collin’s backdrop. So, Alyana, you have a question for the panel?
Palmer: What was your guys’ favorite subject in high school and middle school?
Bailer: Wendy, do you want to start? Martinez: Yeah, I- it’s hard for me to remember. I guess it was- I really liked social studies and of course, I liked the math classes too. So, I guess I would say social studies, history, and math.
Bailer: Yeah so I’m going to say- outside of math and science because I sort of hinted that those were things that I really liked- I really liked history, and I liked archaeology and, you know, we took some classes like that. I liked literature, I love to read, so for me, I liked reading things that were interesting and that I would learn from. I liked a lot of schools, especially the summer months. But I think a lot of the subjects I enjoyed; I would say some of the social sciences as well.
Jennings-Lopez: Collin, do you have a question for the panel?
Dunmore: What is your favorite part of your job? Like the parts that you look forward to the most.
Martinez: You want to take that John?
Bailer: Sure, I think it’s interviews with middle school students because, I mean, what can be better than that? I mean I love being able to work on lots of different kinds of problems. I get to- there was a quote from a very statistician that said the best part of being a statistician is that you get to play in everybody’s backyard. And you know that’s a paraphrasing of a John Tukey quote. And I really do like that. I mean I work with people and, gosh I’ve worked with people that have looked at the formation of fossil records. You know what shelves get destroyed and which ones pass through to be found in the present. I’ve worked with biologists thinking about how do you set water quality standards for receiving waters. I’ve worked with people in education thinking about are the certain curriculum that is better than others? I’ve worked with people in occupational health about what’s the right kind of occupational exposure limits. I mean so for me that part of the job has been just a treat. And you know, I started out a little bit joking saying talking to middle schoolers is a highlight, it really is a highlight. I love working with students, I love interacting about what we do and why it’s fun to do it, so I feel like I’ve been really blessed to have this opportunity to work on lots of different things with lots of different kinds of people.
Martinez: Okay, I guess my favorite thing, at least right now- so, I guess I’m at the management level so I don’t get the time too much, unfortunately, to play with data you know, like I want to. But one of the things I’ve been able to do since I’ve been at the Bureau of Labor Statistics is to kind of forge relationships and networking with other agencies both in the United States and around the world. So, kind of making those connections, you know, sharing information. One of the things I started [inaudible] our user's group, so you know John was talking about the tools that we have available now, so there’s a lot of open-source software that you can use for analyzing data so you have access to those for free, is to be able to forge these connections and relationships so that we could share information and learn from each other. So, that’s what’s kind of nice about talking to both of you because you know I’m learning from both of you believe it or not.
Bailer: So, Wendy, can I follow up with that? Because you’re, you know- have you stopped learning, Wendy?
Martinez: No.
Bailer: Is the practice of how you interact with data and how you interact with statistics and how you interact with computers the same as it was when you were just starting out?
Martinez: No. It’s- yeah we’re always learning. I had a t-shirt once that said the truly educated never graduate.
Bailer: Oh.
Martinez: You can kind of interpret that in a couple of ways. Yeah, I interpreted it as I'm always learning, so, but thank you Alyana and Collin.
Dunmore: You’re welcome.
Bailer: Can I ask them a question?
Jennings-Lopez: Sure.
Bailer: So, I want to know how did you get talked into doing this?
[Laughter]
Bailer: And part of that is you’re part of an after-school data-focused program, is that right? Alyana and Collin: Yes sir.
Bailer: So why did you sign up for that kind of program with the data, and what led you to think about well, gee, I could talk to these stat people about what they do? What attracted you to do that?
Dunmore: Well, I did this last year with Dr. Johnson, so I was already into it, so I don’t think I had a choice.
[Laughter]
Dunmore: I was always going to do it.
Palmer: We were already learning about it in after school, so when Dean Jennings-Lopez asked me I was like, okay I'll just do it because we’re already learning about it.
Bailer: Oh well that’s good. So where do you see yourselves five years from now? What’s your future going to look like five years from now?
Palmer: Graduate and going off to school.
Bailer: Okay and you said you nursing is something you were thinking about, is that right?
Palmer: Yes sir.
Bailer: All right. What about you Collin?
Dunmore: Athletics and if that doesn’t work out I think I’ll probably do life science; that’s probably what I’m most interested in right now.
Bailer: Oh, that’s great. Hey, where’s the stat part of it? Come on.
Martinez: Well, there’s statistics in there, there’s data in there.
Bailer: Right, there's a double major there I know it. I know it.
Dunmore: Sports analysts: that has statistics in it.
Jennings-Lopez: It does.
Bailer: Hey, I’m going to put a plug for Stats and Stories, you know we had the director of sports analytics for the Miami Dolphins as a guest, did you know that?
Dunmore: No sir.
Bailer: Well, there you go. So, you know, you could check it out.
Jennings-Lopez: Yeah, I think that was on the email that Charles sent me.
Bailer: And so, LaToya can I ask you a question?
Jennings-Lopez: Sure.
Bailer: How did you get interested in data and how do you use data in your work?
Jennings-Lopez: Well, so it’s interesting, that’s what I was saying earlier, that prior to my new position I was the Dean here at Howard Bishop and so, of course, I used a lot of data based on services of students’ behavior intervention plans, looking at how we can decrease the behavior, looking at why the behavior is caused, and we also did a survey of what time of day we were having the most problems at the school. We realized that a lot of our problems happen right before lunch and right after lunch. So, we figured that they were probably hungry and was just ready to eat, and then after lunch just kind of excited because now they know they’re closer to going home. So, we realized a lot about things that we need to look at as a school was geared around that time. So, we made sure we had more supervision before and after lunch because we saw that those times were when the kids really just changing their personalities. But now as the director of the Community Partnership School, I live in the world of data now. We are constantly surveying; we collect data daily. Even with the after school we collect attendance, like when we have people in line like Dr. Lee when he talks to the kids, we collect after that to see what they did or dislike. And Changemakers itself, the program itself is data-driven and it has been so successful. This is our second year here at Howard Bishop and we’re just so excited that Dr. Linda and her team, Beatrice, and all of them have just came and just really have changed the face of after-school, but some of the students here in the school itself about data, like it really introduced us to a whole other world. And I would say culturally speaking as an African American, you know, you hear about things in the community, but now I’m able to have conversations with people on a different level of how the information gets there because kids always ask you like how do you know that? Or kids always ask you like for example, well how do you know that that’s not a safe neighborhood to live in? So now I’m being able to say well look at the data and what the meaning is, you know, look at the crime rate report, look at how the community sees the crime rate report. So even having this conversation not only here at the school, but having it locally at my church in the community and I didn’t realize, like I said to you earlier, how much data plays a role in our day to day life. Like you think about- like I said to Alyana earlier about how data affects us. We had a conversation on Friday and I thought she was going to bring it up, maybe she doesn’t want to, but just being a woman, you know, and having to look at jobs and relationships and how we may be treated fair or unfair or however you may see it, and I was just telling her you know, that’s data. Like you don’t realize that it impacts you. And we talked about census a little bit and why it’s important to do the census because it also shows data to bring in things in your community, and also Wendy said earlier sometimes you need to know what you don’t need to know what you do need. And so that’s my spill on that. I’m really excited. Like I said I’m starting to learn more about it. I like the opportunity of being able to have conversations with people such as yourself John and Wendy because it is so important. I’m getting really more into it, and I never thought in my latter years I would be driven by data and interested in statistics because this was not my favorite subject in college. [Inaudible] I got through the program, but now I’m realizing how important it is to use it and I’m constantly even doing it with my- I have a six-year-old daughter and I’m constantly doing things with her, I’m polling her and having her- it was funny, the other day we were talking about a little personal story about how do you know you’re doing things right? And so, my mom, like the older women in my family, my mom they all had passed, so it’s only me and my sister. So sometimes you have that relative you can go back and check and say am I doing this right? So, I asked my daughter a question, I was like do you think I’m doing a really good job as your mom? She was like yeah and she asked me, she was like I feel like you’re giving me a test, why did you ask me that question? And I was like because I need the data. And she was like what do you need the data for? And I was like to know if I’m not doing it right, so then we had a whole conversation about data so she began to tell me about how they had a vote to go outside and the teacher was asking everybody who wanted to go outside and she said to me, she’s like is that data? And I was like yeah that’s a form of data. That’s an informal way of her asking so most of the kids agreed so [inaudible]. So having that conversation at a later date she was talking to my husband and she told my husband – she asked him a question about something and he was like okay and he asked her something like why was she asking him something and she was like I just need the data. So now we reference everything to data now and you know it’s true. You don’t think it like that but- especially when you’re in it, and I’m pretty sure you guys live it, but you are constantly looking at the data. And it’s probably a little different in your mind because you’re constantly looking at it. So when you look at a traffic light and you’re thinking on a whole other level about why that traffic light is here, how it got here, and the rest of us are like oh God I hate this traffic light; it’s so long. But you know the data behind it and probably the statistics to why that traffic light is where it’s at. So that’s my spill on data. Sorry Charles.
Martinez: I think you bring up a really good point that sometimes people think data might just be numbers or, I don’t know, education level or race, ethnicity, but there’s a lot of other types of data that we normally don’t think of as being data and I think that your conversation with your daughter really illustrated that well. And I think that’s fantastic. You said she’s six years old?
Jennings-Lopez: Yes.
Martinez: Oh my God.
Bailer: I’m surprised she didn’t say to you well I’ll tell you in another year; I’ve got to collect more data before I judge the job you’re doing. She could be collecting data too, not just you.
Jennings-Lopez: Yeah, my sister told me that one day it’s going to backfire one day she’s going to say something to you like well the data says that you said… and you’re going to be like stuck with it, but yeah.
Bailer: She might want to have a control group to compare it too. You’ve got to be careful about how this is going to work.
Jennings-Lopez: Right, I think it’s far out of control, but I agree, especially for her and her friends. Bailer: And you also bring up a good point too about the school program you have which is that you know when you are trying to establish something like that or expand it or what have you, that being able to have the data to show what’s working and what’s not working and why it’s good to decision-makers then that often helps you with getting the decision you want, hopefully.
Jennings-Lopez: Right, right. So, any other questions for our panelists at this time? So I would like to thank Wendy, John, and especially I’d like to thank Alyana and Collin for taking the time out in this new normal and your new day, because technically you guys are kind of in school to spend time with us and to make this podcast happen. I really appreciate you. You represented Howard Bishop very well, so Mr. Gamble is going to be very proud of you, and your peers. So good job for all of you. So, any lasting or leaving thoughts you want to end with or anything we want to say to seal the conversation? We’ll start with you Collin, any last words, last thoughts you want to say?
Dunmore: Thank you guys for using your time to meet with us as well.
Jennings-Lopez: Alyana?
Palmer: I just want to say thank you.
Bailer : 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 or 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 on 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.