(This article was originally published at John D. Cook » Statistics, and syndicated at StatsBlogs.)
This week’s resource post lists notes on probability approximations.
Do we even need probability approximations anymore? They’re not as necessary for numerical computation as they once were, but they remain vital for understanding the behavior of probability distributions and for theoretical calculations.
Textbooks often leave out details such as quantifying the error when discussion approximations. The following pages are notes I wrote to fill in some of these details when I was teaching.
- Error in the normal approximation to the binomial distribution
- Error in the normal approximation to the gamma distribution
- Error in the normal approximation to the Poisson distribution
- Error in the normal approximation to the t distribution
- Error in the Poisson approximation to the binomial distribution
- Error in the normal approximation to the beta distribution
- Camp-Paulson normal approximation to the binomial distribution
- Diagram of probability distribution relationships
- Relative error in normal approximations
See also blog posts tagged Probability and statistics and the Twitter account ProbFact.
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