How did you become interested in statistics?
I worked at Frøysa clearing forest underneath the power line; I was hired by my partner – the pay negotiations were tough [Laughs]. I did that for quite a few years. Then I discovered it was time to do something else. I had to take prerequisite subjects for college, and used a year on that while working. It was difficult to do it all by myself, but it worked out. I applied to different engineering college programs, and a one-year land surveyor program at Gjøvik. I got accepted to several of them … and ended up at Gjøvik.
And so I arrived there, Day One, a refresher on trigonometry … sine, cosine were just buttons on the calculator for me – I'd never used them before [Laughs]. But after a while it evened out. After the one-year program I applied for an internal transfer to the bachelor's program in geomatics at NTNU in Gjøvik. That program has R1 math as a requirement, and there was a nice R1 summer course. And I thought that doing math for an entire summer was going to be terrible. But it really wasn't. The folks at home never had as nice a summer as the one where I was studying math either [Laughs].
I began to think about math in a new way – going from a person who memorizes to a person who actually thinks and understands a little, and I began to tackle and use statistics. Because in land surveying you must be able to answer questions like "what is the accuracy of this measurement?" and "how confident are you?". And you must be able to put numbers and words to things like accuracy, precision, reliability, confidence – you must be able to give answers that people will understand.
I've always been pulled towards statistics. That's what I found most enjoyable at Gjøvik too. There we analyzed the base measurements, and it was fun to sit and solve the measurement series. So I get to use my head a little, looking at data series, picking them apart and analyzing them. I have yet to meet a boring data series, and this eventually pulled me completely towards a master's in applied statistics.
If you were to describe your time as a master's student so far?
Awesome, but that doesn't mean that it's been simple or easy. Things can be cool and difficult at the same time. It’s not like you just suddenly think 'eureka' about everything – but what was difficult three weeks ago is a little less difficult today, and you build from that slowly and carefully. So I don't think taking a master's degree is about being clever at school or smart, it's more about being tough enough. You also must want it for yourself. External motivation only gets you so far.
In your master's project you use data collected on students in STAT100, including personality types. Can you tell me a little about your research project?
I can get interested in anything with respect to what I number crunch. You can say that those who know me a little have stopped telling me stories that end with "and what are the odds of that?". Because they don't actually want to know what the odds are, and they certainly don't want to know how to calculate them. So I can get caught up in the most unbelievable things.
With this project, what attracts me is that the data set could potentially be large, and that it is a type of data that I've not worked with before – so, it may be a little unusual, but it’s like "yes, I know nothing about this from before, so I’m sure it'll make a great master's thesis" [Laughs]. I've always found it interesting how two persons perceive the same lecture – how one person just understands everything right away, while another person is just "huh?" – it's interesting to see how people are different. The relevance of the project is particularly attractive. Maybe we can learn a little more about how people learn, and with that advance another step down the road towards a best possible STAT100 for most people.
It's about finding good methods to reveal the message that is contained in the data series. All data series have some message or other. I'd like to see if I can use geomatics as well. If we can manage to model each student as an emotional landscape, and apply geographical analysis techniques to this, if we can use mass calculations, and see how the different students' emotional landscapes differ from each other. Can we group them by emotions? It would be super cool to achieve this. Then we can also see if they can be classified in some way, if we can connect them to personality types. I'd like to see if different personality types have different emotional landscapes.
What would you say to a student starting in the program you're in?
I wish I'd learnt a little earlier that this panic phase at the start of a new study or course – it's completely unnecessary; things usually work out, and you don't need to have everything under control. It's so easy to think that everyone else is cleverer and manages to accomplish so much more than oneself, but we're all in the same rut. I learn very slowly at the beginning of a course, and then things fall into place. So instead of stressing at the beginning, I know that I need to attend lectures, listen, get more information, and then things will usually work out.
Do you have any thoughts about what you'd like to do in the future?
If I had a hundred million NOK in my account, I'd probably become a researcher [Laughs]. I don't actually know. I'm focused on my studies at the moment, so planning what I'm going to do after I'm finished is not a priority – but the future will come. I do hope that somewhere in the world there is a place for a data nerd – I do think that's the case. And if at first I don't succeed I can always fall back on my engineering degree. That's partly the reason why I dared to switch over to statistics – I have a good education to fall back on; so taking this master's degree is something I'm doing for myself.
Lastly, do you have a favorite mathematical or statistical concept that you'd like everyone to know?
I think propositional logic [also known as statement logic] is very interesting. Many parents should be glad that their small kids don't know much about propositional logic. A common statement in the Norwegian home is 'if you tidy your room, you'll get pocket money'. If you tidy your room and you get pocket money, then the statement is true. And if you clean your room, but you don't get any pocket money, then the statement is false. And then if you don't tidy your room, and you don't get any pocket money, the statement is still true. But what happens if you don't tidy your room, and you get pocket money anyway? Then the statement is still true, because nothing has been said about what happens if you don't tidy your room! I think it's funny, but kids shouldn't learn too much about this.
- Interview edited for clarity and length.