I met Liza (pronounced Lie-zuh, like Liza Minnelli) at the R-Ladies meetup in Auckland, New Zealand where she was giving a talk on colour palettes. If you ever meet Liza, you will see that it is absolutely impossible to not get a massive positive energy recharge after talking to her. Liza is currently doing her PhD in Statistics, running a consultancy called The Data Embassy, speaking at events, teaching, mentoring. It would be my absolute pleasure to learn more about Liza and share her wonderful story.
I’m currently in what I’m calling the ‘end times’ and planning to submit in the next few months. The main goal of my research is to understand how patterns of social and economic experiences across New Zealanders’ lives relate to mortality. For example, does going from having a ‘higher status’ job to a ‘lower status’ job change your risk of dying? Is it different for males and females? I also want to understand whether there are social or cultural factors that might help protect against risky social and economic situations, and whether differences in these patterns can help explain the still large ethnic disparities in mortality in Aotearoa. I hope a better understanding of these questions may prove useful for developing public policy.
There are so many people to thank for spurring my enthusiasm! I’m an accidental statistician—I did Statistics in my final year of high school and liked it, but was planning to go to university to be a physicist. 17 year-old Liza loved her some quantum physics. I only really took a course in statistics at the University of Auckland because I wanted to honour my high school stats teacher (hi, Mr Crombie!). I had the very good luck of having Ilze Ziedens as a lecturer for that first course. Seeing someone who clearly really enjoyed what they did and was doing useful work in the world (optimising the order people get seen in health care settings can literally save lives) made a big impression on me. She also gave out chocolate, which made an even bigger impression. I took more courses in stats and fell more and more in love. You’re welcome to accuse me of bias here, seeing as I’ve been a lecturer there myself, but I really have to credit the awesome teaching culture, and culture in general, of the Department of Statistics. Interesting people who care about their work and their students and making the world a little better? Hard not to get hooked!
I think my timing was so lucky, too, because there has been such an explosion of cool and useful data related stuff to get excited about, including the nascent data journalism scene in New Zealand. I have literally had a sore face from smiling for an hour in a seminar Harkanwal Singh did on data visualisation.
Will you kick me out of this interview if I admit to not only being an accidental statistician, but an accidental entrepreneur, too? The first project I worked on was referred to me based on work I’d done in the Mathematics Department for a summer scholarship. I was so excited to do something real that I hadn’t even thought about what my fee should be. When the client asked, I said something like “Well, I get about $20 an hour for tutoring…”. Now, I wouldn’t have blamed him for agreeing to that, but he paused and said “We’re going to pay you more than that. Why don’t you ask around and come back to us.” Figuring out how much I’m “worth” is still really hard for me. I’m grateful to folks who have been happy to talk about their fee structures when I’ve spoken with them as having reference points really helps. If anyone wants to get in touch, I’m happy to pay that transparency forward and tell them where my fee structure is at now and how I got there.
Another challenge has been self / professional-doubt. When you’re working alone for a client who has to just trust you that the analysis plan you’ve proposed makes sense and is appropriate...well I worry a lot about getting it right. It has been nice, as I’ve done more projects, to have validation through peer review and have work I’ve done stand up to inspection. And I think in moderation it is healthy to not be too overconfident and stay vigilant for mistakes.
A more recent challenge has been how to better mentor and support other up-and-coming statistical consultants. It is something I’m really keen on, but still figuring out how to balance that with my thesis and other projects. I’ve loved running my little company and working with fantastic clients, and it has helped me grow so much, that I hope I can set a few more accidental and not-so-accidental entrepreneurs on this path, too.
If students leave my class at the end of the semester with only one thing, I hope it is a better honed bullsh*t detector. Statistics is such a useful tool for thinking better. Good statistical thinking overlaps with psychology and behavioural economics through the biases we tend to let go unchallenged and that can cause us to make bad decisions (book recommendation: Thinking, Fast and Slow by Daniel Kahneman). Statistical thinking can help you be a more critical consumer of news, which feels more important than ever.
Two examples of stats communication-y work I’ve been a part of in recent years span from the fearsome to the frivolous. In the fearsome (but overblown) category was the Cambridge Analytica scandal, in 2018, where a company was using ill-gotten Facebook data to supposedly sway elections. I think a lot of people found what they were hearing really scary, and don’t get me wrong, privacy is a serious issue, but a bit of stats knowledge made it pretty quick to see the company was probably claiming to be able to do a lot more than they really could. More stats knowledge, less unnecessary fear.
The frivolous example, and surely the main reason stats folk ever get to do interviews, is the lotto. Firstly, don’t play lotto. Almost-a-Doctor’s orders. But if you are going to anyway, and don’t want to share first division 40-ways...don’t pick pretty patterns. Or your mum’s birthday.
The thing I’m most grateful for learning, and that I didn’t expect, was that falling in love with statistics would provide a pathway to really be my whole and happy self. So who am I? I’m a nosey, occasionally creative, drama nerd, that likes making bad jokes, helping people and solving problems.
In high school I was a drama nerd and loved public speaking. Lecturing in a big classroom has the fun of being on stage, but improved by getting to interact with students, make ‘dad jokes’, occasionally do Harry Potter dress-up or wear a rainbow tutu, and facilitate ‘aha!’ moments which are basically my drug of choice. There are enough stats enthusiasts out there that I can design and sell nerdy stats t-shirts as a creative outlet. I’ve always been curious about the world (read: nosey) and statistics helps me understand and explore the patterns around me. I like solving problems and I like helping people, and lots of people have statistics problems they would really, really like help with. There is also a special kind of beauty and satisfaction in an elegant proof or bit of programming, and a totally different but also wonderful satisfaction in helping someone who thinks they hate numbers feel more comfortable and confident. I’m still working on bringing together dance and statistics...but I did do a normal distribution dance in my job interview (and they still hired me!), and would someday like to build that into a whole stats distribution Zumba routine...
Bonus unexpected fact I’ve learned: The pain centres of the brains of people with high maths anxiety activate when they anticipate doing maths, but not when they’re actually doing maths! (Don’t believe me? A summary of the research is here.) Maths won’t hurt you, but thinking about doing maths might.
In July 2018 I was very lucky to be in Kyoto, Japan for a statistics education conference. My colleague / mentor / co-avid stats education enthusiast Anna Fergusson—who is one of those wonderful people who lifts up the people around them—had involved me in research she was working on and suggested I come along to co-present it. Thanks to Twitter, I’d connected with some Canadians who were also at the conference and we went out for lunch. (Twitter is actually great for conferences and the stats community in general on there is pretty awesome.) A bit of background: I was born in Canada and have lived half my life there and half my life in Aotearoa New Zealand. At the time of this conference, my partner, Steven, and I had been talking about next steps for our careers and growth as people, and had been considering a move to Canada. From there the stars just aligned. I loved the people I met from the University of Toronto and it turned out that they were going to be advertising a Teaching Stream role soon. ‘Teaching Stream’ meant I’d get to focus on teaching, outreach and stats education research, the stuff that makes me most excited to get up in the morning. I interviewed in January this year and got to show Steven around Toronto and then was offered the role in February.
I am really looking forward to teaching a first-year data science course when I get there, and being in a department where there are 4,000 students minoring, majoring or specialising in Statistics. That’s gigantic! I also hope I can continue some of my research interests in what we can do better for indigenous students in statistics. And perhaps most of all, I’m looking forward to working with and learning from the other members of the department. People and department culture matter a lot to me, especially as I’ve been so spoiled by the awesomeness of my current department. And I believe good culture supports better teaching and research.
Mental health. Mental health is the biggest thing I worry about for my students. How do we, as lecturers and institutions, hit the right mix of challenging and extending students as well as supporting them and accommodating a range of needs? I don’t have a clear answer, but I want to improve my knowledge and skills. And as in most things, empathy and making authentic connections seems like a good start.
If you can be lucky and like something that is useful, but that a lot of other people don’t like, you’re pretty well set. And how can you help make your own luck of that kind? Approach things with an open mind, meet people who love what they do, and don’t let narratives of what you should like, or be good at based on your gender or ethnicity or anything like that, block off paths for you. I am glad I didn’t realise “girls are bad at maths” until it was too late and I loved it.
Well, the last three books I read* were Walden (Henry David Thoreau), Fooled by Randomness (Nassim Nicholas Taleb) and United: Thoughts on Finding Common Ground and Advancing the Common Good (Cory Booker). So in two words, I’m thinking about gratitude and luck. In more words, I’m thinking about how being more minimalist and reflective can free us to joyfully give the hard work and courage necessary to do good in the world, while remembering that randomness is always at play in our complex and interconnected lives and thus no success (or failure) is wholly in our control, and so we should be gentle with ourselves and others.
*Well, listened to, I’m loving being able to borrow audiobooks from the library on my phone!
Any of the folks doing data journalism in NZ - Kate Newton (RNZ), Keith Ng (the Herald), Chris Knox (the Herald), Harkanwal Singh. Academics like Lara Greaves (Politics), Analosa Veukiso-Ulugia (Social Work), Hinekura Smith (Centre for Learning and Research in Higher Education (CLeaR)) who are inspirational badasses working towards changing systems that aren’t serving Māori and Pacific students. Academics in STEM that are working on making better systems for women and LGBTQ+ folks, like JJ Elridge (Physics), Nicola Gaston (Physics) and Kate Hannah (Te Punaha Matatini). And any of my evidence-based heroes at the Workshop, especially Tze Ming Mok and Jess Berentson-Shaw, whose book (A Matter of Fact: Talking Truth in a Post-Truth World) is the book I’ve given as a gift most.