What You THINK You Already Know
I started Taekwon-Do when I was an undergraduate in college. If you are familiar with martial arts, you know that Taekwon-Do is notorious for flashy kicks and weak hand techniques. My school was different. The head Master was a former Golden Gloves Boxing champion and spent much of his career as a corrections officer breaking up prison fights. Though he could practically levitate with a 360-hook kick, he was more pragmatic in his teaching. I still remember him saying, “If you have solid hands, four basic kicks, and you can land them accurately, the fight doesn’t last long enough for you to jump.”
These days I spend more time punching in data analyses than bags, but the dedication to the basics that I learned in Taekwon-Do serves me well. While I appreciate and marvel at the insights that can be garnered from structural equation models and hierarchical linear models, I’ve been spending my professional development time re-learning the basics of statistics — correlations, t-tests, chi-squared, etc. The scaffolding of those more advanced models is built by the basics of these stats 101 tests. The more I know them, the more I understand about the advances — and limitations — of the fancy models.
After years of practicing any profession, it can be easy to take the basics for granted. To see the beginner texts as something you’ve checked off your list. But if you go back and give them another look with your more educated eyes, I guarantee you will see things that you missed. Things that will change how you see and practice what you do.
A person learns something new by associating it with what they know. What you know now is inevitably worlds apart from what you knew then. What is it that you think you know? What fundamental skills and knowledge do you take for granted? Give those intro texts a fresh look. You’ll be surprised by how much more you have to learn.
