The score, of course, is the main dependent variable in golf. In stroke play (the most common form of keeping score) the player who takes the fewest strokes wins. In match play, the player who wins the most holes wins.
Over the last five years, I have discovered other golf dependent variables. One is the net number of balls lost or found. If I find more lost balls than I lose, I win. Another dependent variable is the number of pars (birdies if you are good or bogeys if you are not) per round. Other interesting dependent variables are how straight the ball flies or how far it goes.
Lately, my experimentation is progressing nicely. Golf being what it is, I should expect a sudden and rapid rise my stroke count.
Golf is also a good way to approach statistical topics. In class, I like to show the difference between my golf game and Tiger Woods'. Tiger has a MUCH lower standard deviation than I do for both direction and distance.
The good news is I am bringing my SD down for both distance and direction. Last week, I told a colleague about playing in the early morning fog. He asked me if I could tell whether or not the heavy, foggy air was making my shots shorter. I replied that my SD was still too big for me to answer that question. In other words, the distance I hit the ball is still too variable to conduct an experiment using the independent variable of air density.
To answer his question, I'd have to hit the ball the same distance and direction every time. Then, if I did that when the air was dry and the air was foggy, I could answer his question. There is a way to do that; use a machine to hit the ball consistently.
One machine that does that is called the Iron Byron:

Now to figure out how to acquire an Iron Byron and get some one to pay for my golf research.
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