9: Central Limit Theorem
( \newcommand{\kernel}{\mathrm{null}\,}\)
- 9.1: Central Limit Theorem for Bernoulli Trials
- The second fundamental theorem of probability is the Central Limit Theorem.
- 9.2: Central Limit Theorem for Discrete Independent Trials
- We have illustrated the Central Limit Theorem in the case of Bernoulli trials, but this theorem applies to a much more general class of chance processes.
- 9.3: Central Limit Theorem for Continuous Independent Trials
- We have seen in Section 1.2 that the distribution function for the sum of a large number n of independent discrete random variables with mean μ and variance σ2 tends to look like a normal density with mean nμ and variance nσ2. Let us begin by looking at some examples to see whether such a result is even plausible.