For convenience, we present a short list of elementary statistical terms and formulae.

Statistics as a science deals with mathematical methods of collecting, summarising and analysing data and presenting results of analysis in a mathematical form.

A population (sometimes called a universe) is a set of objects to be studied. The purpose of a statistical analysis is to draw conclusions about a population. In most cases, statistics is concerned with a particular population characteristic called a parameter of the population.

Statistical methods can be applied (only) in situations when it is impracticable or impossible to collect information about all objects in the population but the information is available for a subset of the population called a sample. The process of estimating or predicting population parameters using sample data is called statistical inference.

A sample is described as representative if it is believed that it fairly and comprehensively represents the population from which it is drawn. A sample is biased if it over-represents or under-represents a particular population group. The words ‘unbiased’ and ‘representative’ are usually interchangeable. Both are relative terms, not absolute. Except in highly artificial situations no sample will be representative in every respect. The terms are sometimes used to describe the intentions of the sampler or the design of the sample rather than the outcome.