ABSTRACT
This chapter looks at the basics of statistical inference using computation — to avoid probability calculations — to produce answers. Statistical inference is the process of drawing inferences about a population based on data sampled from the population. Though one informal description of insanity is “repeating the same action while expecting a different result,” in simulation, due to the randomness, repeating a simulation can give us great insight into the distribution’s shape, its tails, its mean and variance, and related probabilities. For the normal distribution both the median and the mean describe the center, as the distribution is symmetric. The key to the basic bootstrap method is to treat the new samples as simulated random samples from the actual population. The exponential distribution is an example of a skewed distribution.
