Random sampling
A random sample of a dataset is a subset whose elements are randomly selected. The given dataset is called the population and is usually very large; for example, all male Americans aged 25-35 years.
In a simulation, selecting a random sample is straightforward, using a random number generator. But in a real world context, random sampling is nontrivial.
Random sampling is an important part of quality control in nearly all types of manufacturing, and it is an essential aspect of polling in the social sciences. In industrial sectors such as pharmaceuticals, random sampling is critical to both production and testing.
To understand the principles of random sampling, we must take a brief detour into the field of mathematical probability theory. This requires a few technical definitions.
A random experiment is a process, real or imagined, that has a specified set of possible outcomes, any one of which could result from the experiments. The set S of all possible outcomes is called...
