18.6 Being More Quantitative
In Nate Silver’s excellent book on forecasting, The Signal and the Noise, he urges readers to “make a lot of forecasts. You may not want to stake your company or your livelihood on them, especially at first. But it’s the only way to get better.”2
We encourage you to take the same mentality, and apply it to quantitative analysis.
What aspects of your own daily life can be quantified? Thanks mainly to smartphone and smartwatch apps, there are lots of ready options – for starters, we could suggest discretionary spending, nightly sleep total, water consumption, or minutes per day spent on TikTok. Any of these could work well – and so can another favorite of ours, daily step count.
Chances are, your phone already tracks your daily step count – and even if it doesn’t, you can download a free app that will do it. Any app that automatically tracks and stores step counts solves three very important problems with data collection – it protects you from the risk of forgetting to do it, saves you from the hassle (and likely irregularities) of needing to count each step, and it also solves the problems of data storage and transcription (straight to your phone is a better proposition than scribbling on a Post-It note or the back cover of today’s newspaper, only to *maybe* record it later on a spreadsheet!)
Start with some data gathering. How many steps do you typically take in a day? Use a few days’ worth of measurements to establish that baseline value. Until you have done that, it’s hard to meaningfully interpret
From there, you could move into some descriptive analytics. Are you a hybrid worker? If so, how many more steps do you take on commute days, vs. your ‘stay at home’ days? Do errands and activities bring your step count much higher on the weekends, or do you tend to retreat into ‘couch potato’ mode on those days?
You could set up some homemade ‘mini-experiments’ now. If you took the stairs rather than the elevator for all the trips outside your building on the stay-at-home days, could you increase your step count by 10 percent? If you pace up and down a few times on the train platform, rather than just standing in one spot as you mindlessly scroll through your phone, can that add another 1000 steps per week? Be the designer, and the subject, in your own research – make a hypothesis, and test it!
Track your results. Store them in a spreadsheet, or as a Python dataframe. Practice your visualization skills by plotting your data. Iterate through various types of graphs to find the one that you think works best for your purposes – along the way, play around with the color schemes, the axis labels, and the display.
Similarly, you can improve your coding skills through consistent, daily effort. We have found that students can keep their motivation level high for longer periods of time when they use sites with interactive lessons and challenges. Rather than endorse any right here, we’ll trust that you can find a few of these with a search or two.
In time, you will see yourself becoming more quantitative. Much like starting a regimen of bicep curls would make your arms stronger, an intentional effort to incorporate analytics into your daily life will shape your quantitative “muscles.”
2 Silver, Nate. The Signal and the Noise. New York: Penguin Press, 2012