If you know me at all, you know how much I love data. Numbers upon numbers all jumbled together looking for meaning. After discovering that FSI is really just a giant social experiment, I decided to start tracking my own numbers for shits and giggles and good time in Excel. So what did I discover?
Well I discovered my body is pretty damn predictable. Since October I’ve been tracking when I consciously let out a giant yawn in the third hour of morning class. That yawn signals the exact moment I lose all semblance of focus and my brain turns to mush. There are a number of variables which impact the timing of my loss of focus. While I cannot track their exact effects on my yawn size, I can acknowledge their existence. So here’s to you variables!:
For the award of most likely to skew the data earlier: How long I slept the night before! Congrats.
For the award of most likely to extend the data later: Amount of caffeine consumed! Bravo.
For the award of most likely to cause a premature data point: Boring class topics! Always a winner.
For the award of most likely to have some unknown effect on the data, we have a three way tie: temperature in room relative to what I am wearing, if someone else has yawned, and amount of studying that occurred the night prior.
So, what did my lovely data sample tell me? It told me “I’m just a sample, geez! Back off!” It also told me to keep tracking, because I know it happens daily. I also need to track the days I don’t yawn, so I can analyze what I did the night before. My data had one outlier, which I promptly discounted because it was the first data point ever recorded and I don’t think I trust it. Therefore, out it went. Because you see, the Foreign Service hires us for judgement and I just assessed that data point as untrustworthy and I can just toss it aside. Also, I vaguely remember just guessing. My data points also told me that I’m fairly consistent. Let me backtrack real quick and give you an idea of my method, because you know, science. So, I took the time I logged as my first yawn and entered it with the date into Excel. I then subtracted the time class started from the time I logged. I multiplied all the times by 24 and 60 to get the minute, that way I had an exact numerical digit to play with. I then averaged my sample, calculated sample size percentage based on work days, variance, and standard deviation. I plotted the data points and hoped to god for a regression line. Apparently god doesn’t grant pretty data regression wishes.
My average time from the start of class to my first yawn was 148 minutes. Which puts it exactly at 10:08am, which also happens to be the median. Don’t you love when that happens?!
The variance was 14, meaning my data only varied by 14 minutes between the earliest recorded time and the highest.
My sample size was 11 out of 58 work days. Although I only really started recording in Phase 1, which started in October. So if we adjust for that, my population is actually only 38 days starting at Phase 1. That means my data represents 29% of the population, all workdays being equal. See how much fun it is to manipulate numbers!
My standard deviation was 3.79, which means at least 95% of my data falls within a 3.79 minute window of my average: 10:08am. So my big yawn occurs primarily between the times of 10:04 am and 10:12 am, rounding.
Here’s the plot:
As you can see, the data looks like a mountain pass. And the regression line does absolutely nothing because the data sample size is relatively small with the range of values. Also, it just doesn’t work, so there’s that. This just ain’t the tool for the job.
But here is the takeaway from all these fun numbers: I become tired after about 148 minutes of class. Therefore, if anything important needs to be discussed or learned, it needs to be before that cutoff. Anything after those 148 minutes should be review, otherwise, oh hell no, it ain’t sticking.
I’m going to keep tracking and adding sample points to my data so I can continue to distract myself from what I should actually be doing, studying.