Statistical methods are particularly useful for studying, analyzing, and learning about populations of experimental units.
|An experimental (or observational) unit is an object (e.g., person, thing, transaction, or event) about which we collect data
|A population is a set of all units (usually people, objects, transactions, or events) that we are interested in studying.
Examples of populations:
|A variable is a characteristic or property of an individual experimental unit in the population.
Examples of variables:
It is nearly impossible to measure each grain of sand on a bench, so instead of collecting the population, we can estimate using a sample.
|A sample is a subset of the units of a population.
|A statistical inference is an estimate, prediction, or some other generalization about a population based on information contained in a sample.
Examples of statistical inferences:
However, the accuracy of the statistical inference depends on how reliable it is.
|A measure of reliability is a statement (usually quantitative) about the degree of uncertainty associated with a statistical inference.
Statistics by Matthew Cheung. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.