23. Video: Bootstrapping & The Central Limit Theorem
Bootstrapping & the Central Limit Theorem
You actually have been bootstrapping to create sampling distributions in earlier parts of this lesson, but this can be extended to a bigger idea.
It turns out, we can do a pretty good job of finding out where a parameter is by using a sampling distribution created from bootstrapping from only a sample. This will be covered in depth in the next lessons.
Three of the most common ways are with the following estimation techniques for finding "good statistics" are as shown previously:
Though these are beyond the scope of what is covered in this course, these are techniques that should be well understood for data scientists who may need to understand how to estimate some value that isn't as common as a mean or variance. Using one of these methods to determine a "best estimate" would be a necessity.