- Simplicity, Simplicity, Simplicity
Picking a feasible topic is the first, and maybe hardest, hurdle to overcome during anyone’s thesis process. This is especially so if you’re doing quantitative research for the first time. Not a single person in my V-491 class succeeded at this the first time, or the second time, or even sometimes the third time. Many people I knew, including me, were still working on challenging tasks for our skill levels and resource allocations until the last month or two of the thesis process. The difficulty of independent data analysis and research is not fully evident until you actually do it. So my advice would be, think of a topic that really interests you, and you’re curious if there’s any kind of correlative link between different variables. Now cut the scope of that in half. Now cut the scope in half again. Now simplify the variables you’re including until you’re only looking at one specific piece that may influence or make up your original idea. Now you have a feasible topic.
Here was my diagram tree for my indepdent variable (IV) to my dependent variable (DV). I ended up simplifying it to the correlation between compulsory voting policy to voter turnout, political informedness, and political participation. Everything to the right of my first two mediating factors was cut, and even then, I still didn’t have the statistical abilities to complete what I did to the extent I would’ve liked to.
![](https://blogs.iu.edu/cari/files/2023/04/Screenshot-2023-04-27-124146-300x180.png)
- Building Quantitative Research Skills Before V-499
That last statement brings me nicely into what I thought was the most important factor that allowed me to even complete my thesis, independent work during winter break. Those three weeks were crucial for me as someone doing a quantitative research project with no quantitative experience. And I proved it is possible, with the right help and mindset. I dedicated about 2-3 hours a day during winter break to just learning the basics of STATA (a lot of the time R is not necessary to complete basic linear regressions). And I did this on top of a full-time job, which I don’t mention for the sake of bragging about my work ethic; I will be the first to admit I can be overly-lazy and procrastinate at times. I only say that to emphasize that there’s no excuse for not being able to learn basic statistical packages, no matter what your other time commitments are. Give up your free time for a month; apply yourself, and you’ll be surprised by what you can accomplish.
I’d also like to point out it didn’t necessarily have to be that way. Taking SPEA K-300 is important for gaining knowledge of basic statistical concepts, but you need more than that for even the simplest quantitative analysis. I would say SPEA V-370, Research Methods and Statistical Modeling, is a must-have, at least from what I’ve heard from fellow public policy students. V-491 replaces the requirement for that class for law and public policy majors, which is why I never took it. But my non-honors classmates explained it as a boot camp of sorts for statistical analysis skills, ones I sorely wish I’d had when working with STATA. So in summation, if you take V-370 (and I’d perhaps recommend even finding another statistics class to take on top of that) before V-499, you’ll have a much easier time than I did working through whatever statistical package you’re using to run your regressions.
Matthew McClarnon is a senior in the O’Neill School of Public and Environmental Affairs majoring in Law and Public Policy with a minor in International Economics.
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