Simulations in R
So the key is to compare Kobe's data with that of a shooter who we know to have independent shots. While we don't have any such data, that is very easy to simulate in R.
In a simulation, you set the ground rules of a random process and then the computer uses random numbers to generate an outcome that adheres to those rules. As a simple example, you can simulate flipping a fair coin with the following commands.
outcomes <- c("heads", "tails")
sample(outcomes, size = 1, replace = TRUE)
The vector outcomes can be thought of as a hat with two slips of paper in it: one slip says “heads” and the other says “tails”. The function sample() draws one slip from the hat and tells us if it was a head or a tail.
Don't worry if you don't completely understand the code right now. We'll explain it throughout the remainder of this lab.
This exercise is part of the course
Data Analysis and Statistical Inference
Exercise instructions
Paste the second command listed above several times in the editor and hit Submit Answer. Just like when flipping a coin, sometimes you'll get a head, sometimes you'll get a tail, but in the long run, you'd expect to get roughly equal numbers of each.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Try some simulations!
outcomes <- c("heads", "tails")