Written by: Spencer Greenhalgh
Primary Source: Spencer Greenhalgh
This episode of Spencer Writes in the Library took place Thursday, March 19th around 1:00pm.
Where am I working today?
I’m deep into the stats part of my practicum right now, so I’m actually in the MSU math library in search of a book that I’m hoping will clear something up (spoiler alert: not really).
What’s a perk of this spot?
It’s a new place to be. I’d always assumed that most of my MSU Library exploration would be in the Main Library, but this is opening my eyes to other possibilities. The math library is also closer to my “home base” than the main library, so if I only need somewhere to write and read for a few minutes, this might be the spot.
What’s a problem with this spot?
I don’t feel quite at home here. Part of that is because the best nooks and crannies have already been claimed, so I’m sitting in a spot where I wouldn’t want to stay for several hours to get to work. The other part of that is that being in the math library makes me feel like I’m going to get kicked out as soon as someone finds out my only degree is in French.
What have I learned in this spot?
I wish I’d taken more time to look at it, but there was a neat display about Alan Turing here. I’ve always been interested in the Bletchley codebreakers, so this just reaffirmed my need to learn more about Turing and his colleagues. Also, is that a pocket-sized Enigma machine?
How would I rate this spot?
1 out of 5 dentists. (Why dentists?)
What am I working on today?
The goal for today was to figure out enough about the stats I’m going to use in my practicum that I could finish up another draft of my proposal and send it to my advisor. I ended up running into a couple of questions that I didn’t know I had, which sent me back to the drawing board a couple of times.
What’s the highlight from today’s work?
Well, I certainly feel like I have a better grasp of component analysis right now that I’ve spent a few hours reading up on it in my stats textbook. The problem, though, is that this has left me with a big question that I’m not ready to answer until I have another chat with a stats consultant.
To be honest, I’m having a hard time with (but developing a new appreciation for) quantitative methods. I can do math—I did well in high school calculus and in both of my graduate-level stats courses—but I’m realizing that to effectively do quantitative research, I need an understanding of the theoretical underpinnings of all of these formulas. That’s proving harder than I anticipated, but I think I’m getting closer. Maybe.
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