I think I have a handle on what bootstrapping is and why we need to use it.
Please confirm if my understanding is correct:
Goal of bootstrapping: To find the SE of a feature’s coefficient that you estimated in your ML model.
Background: We have an Original dataset of n = 3. We ran a ML model on it and came up with a coef value for B1. This coef value is just a guess as of now. How do we determine how “correct” is this coef value?
Bootstrapping Steps:
Randomly select 10 observations (w/ replacement) from original dataset. Lets call this Bootstrapped Dataset #1.
Calculate B1 from Bootstrapped Dataset #1.
Repeat steps 1 and 2 100 times.
Now we have 100 B1’s from Bootstrapped Datasets #1-100. Calc the SE of those 100 B1’s. This represents the SE of B1 in the Original dataset.
Yes I inserted numbers like 10 and 100 to make things simpler and easier to understand vs. mathematical notation. I understand that this would be done n times in the real world.