I’ve always liked scientific vocabulary, because it can be used to describe incredibly important and useful data with an economy of terms. But sometimes it’s fun to borrow these terms and incorporate them into your regular conversation, and I support anyone doing this without reservation.
So without further ado, here are some very useful graphs and data tools that can easily be co-opted to communicate very useless information.
These are graphs you may remember from pre-calculus, and they oscillate between high and low values, pretty much into infinity. Most recently, I’ve felt that a sinusoidal curve is really the best way to illustrate a phenomenon I know many others have observed. This includes ocean waves, sound waves, and my friends’ quadrennial fascination with soccer:
A classic. I’m sure you’ve interacted with some kind of likert scale or other in the past week. It’s a useful way to rank similar statements, and then get a personalized score of how you feel about these statements as a whole. Generally, Likert scales are rated with numbers, with low numbers meaning something, and the high numbers meaning their opposite. For a long (long!) time I ranked everything in my life on a scale of 1-3, with one being awful and three being fantastic. But then I visited a friend whose mother had a margarita blender. A margarita blender is just a regular blender, but instead of having settings that go from power level 1 to power level 3, it has a dial that goes from “Siesta” to “Fiesta” all the way to “Arriba.” It is also worth noting that the top of this blender was shaped like a sombrero. Anyway, these functions became the default scale for all of the Likert Items that comprise my daily life.*
*Note: replacing the numbers in a Likert scale with terms kinda defeats the whole purpose, as now you can’t sum up any of the values for formal data analysis. But using my daily goof-off ranking data in any kind of formal way is too Siesta to even be discussed here on this platform.
This is a wonderful chart that demonstrates how something may be more likely at its smaller or larger form than it is at its average. One classic example is shoe size in the population. If you mapped the nations shoe sizes, and didn’t separate out the population by gender, you’d probably see two spikes. One representing average for female feet, and another representing average size for male feet. You wouldn’t see too many people who had shoe sizes halfway between where the majority of men are and where the majority of women are.
Feet aside, here is a bimodal distribution of how many times, on average, I might ask to touch your hair depending on its length. If you are my friend and I’ve stopped asking to touch your hair and I just do it anyway, I’m sorry. And thank you. You’re very patient. Also what kind of conditioner are you using???