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. |