Fundamentals of Statistics 1: Basic Concepts :: A Parameter and a Statistic
In applied statistical work we rarely have the opportunity to measure entire populations, instead we make inferences about the populations from samples drawn, ideally randomly from the population. We usually want to know averages from whole populations, but use the average from a sample as our best guess at the population average. The unknown population average is called a parameter. The known sample average is called a statistic. It's easy to remember because of the alliteration Parameter: Population and Statistics : Sample. Parameters and statistics are often means, but they could be standard deviations, medians or proportions.

For example, let's say we're interested in improving reading speed and want to test to see if a new speed-reading technique actually works while still allowing for sufficient retention of material.

As a matter of convention, most statistical texts use greek symbols for population parameters and the English or Arabic letters for sample statistics. For example, a sample mean is often denoted as x-bar . Population means are denoted with the lower-case greek letter mu μ . I try and stick to that convention on this website as well (it's just a pain sometimes getting those special characters into HTML).

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