Glossary of statistical terms

Population:

A population is a large set of objects of a similar nature - e.g. human beings, households, readings from a measurement device - which is of interest as a whole. A related concept is a sample , a subset of objects is drawn from a population.

An important broad class of problems in statistics is concerned with making some conclusions about a population as a whole, when you only have a random sample from this population.

In mathematical statistics, analytical tools are developed mainly for infinite populations. If the population at hand (that is usually finite) is many times larger than the sample, then the infinite population formal model is quite adequate.

A population is not necessarily real - it may be hypothetical or imaginary. For example, outcomes of an experiment , that is carried out infinitely, make a hypothetical population. The goal of inferential statistics is to make conclusions about such a hypothetical infinite population from a finite sample obtained by repetition of the experiment or measurement a finite number of times.

For example, tossing a coin infinitely gives rise to a hypothetical population consisting of "heads" and "tails". If a coin has been tossed a finite number of times, say, 100, then one has at hand only 100 outcomes, say, 55 tails and 45 heads. These 100 head/tail values comprise a sample from the infinite imaginary population.

See also: random sampling , sampling frame , and short courses

Browse Other Glossary Entries



Want to learn more about this topic?

Statistics.com offers over 100 courses in statistics from introductory to advanced level. Most are 4 weeks long and take place online in series of weekly lessons and assignments, requiring about 15 hours/week. Participate at your convenience; there are no set times when you must to be online. Ask questions and exchange comments with the instructor and other students on a private discussion board throughout the course.


Statistics 1 - Probability and Study Design

This course, the first of a 3-course sequence, provides an introduction to statistics for those with little or no prior exposure to basic probability and statistics.  It runs every eight weeks.


Introduction to Statistics 1 AP: Inference for a Single Variable

To provide an easy introduction to statistical inference for a single variable. Once you've completed this course you'll be able to apply statistically valid designs to basic studies, and test hypotheses regarding proportions and means.


Introduction to Statistical Modeling

This course provides a solid introduction to the ideas and techniques of statistical modeling.


Sample Size and Power Determination

This course shows you how to make sample size determinations for various statistical tests and for confidence intervals, as needed for experimental studies such as comparison studies, as well as for other types of experiments.


Maximum Likelihood Estimation

This course will cover the derivation of maximum likelihood estimates, and their properties.


Ecological and Environmental Sampling

This course covers sampling methods and analyses used to study of the density and abundance of animals and plants, and other important biological variables.



Back to Main Glossary

Promoting better understanding of statistics throughout the world

To celebrate the International Year of Statistics in 2013, we will provide a statistical term every week, delivered directly to your inbox. The Institute for Statistics Education offers an extensive glossary of statistical terms, available to all for reference and research. Make it your New Year's resolution to improve your own statistical knowledge! Sign up here. Rather not have more email? Simply bookmark our home page and check our “Stats Word of the Week” feature.
Want to be
notified of future
course offerings?
Please enter first name.
Please enter last name.
Please enter valid E-mail.
© Statistics.com 2004-2014