The document describes various probability distributions that can arise from combining Bernoulli random variables. It shows how a binomial distribution emerges from summing Bernoulli random variables, and how Poisson, normal, chi-squared, exponential, gamma, and inverse gamma distributions can approximate the binomial as the number of Bernoulli trials increases. Code examples in R are provided to simulate sampling from these distributions and compare the simulated distributions to their theoretical probability density functions.
The document describes various probability distributions that can arise from combining Bernoulli random variables. It shows how a binomial distribution emerges from summing Bernoulli random variables, and how Poisson, normal, chi-squared, exponential, gamma, and inverse gamma distributions can approximate the binomial as the number of Bernoulli trials increases. Code examples in R are provided to simulate sampling from these distributions and compare the simulated distributions to their theoretical probability density functions.
The document discusses indexing in different languages and with LaTeX. It provides examples of indexes in English, Portuguese, Russian, Korean, Thai, traditional and simplified Chinese, and Japanese. For Japanese, the index is arranged by kana and gojuon order rather than alphabetically. It also discusses how to create indexes in LaTeX, including using a morphological analyzer to determine kana, and tips to avoid a messy manuscript. Good indexes help readers find specific information, understand the book's contents, and grasp another perspective, while bad indexes confuse and force readers to read the entire book.
