Everything's got its own lingo, and statistics is no exception. Some of the most common terms used in statistics include the population, sample, parameter, and statistic — also referred to as the big four. Here, you'll gain an understanding of these terms and the context in which they're used. You need to be able to pick out the big four in every situation; they'll follow you wherever you go.

Consider the following example: You're interested in knowing what percent of all households in a large city have a single woman as the head of the household. To estimate this percentage, you conduct a survey with 200 households and determine how many of these 200 are headed by a single woman.

## What is the *population*?

A *population* is the entire group you're interested in studying. The goal here is to estimate what percent of *all households in a large city* have a single woman as the head of the household. The population is **all households,** and the variable is whether a single woman runs the household.

## What is the *sample*?

The *sample* is a subset drawn from the entire population you're interested in studying. So in this example, the subset is the **200 households selected** out of all the households in the city.

## What is the parameter?

A *parameter* is some characteristic of the population. Because studying a population directly isn't usually possible, parameters are usually estimated by using statistics (numbers calculated from sample data). In this example, the parameter is **the percent of ****all ****households headed by single women in the city.**

## What is the statistic?

The *statistic* is a number describing some characteristic that you calculate from your sample data; the statistic is used to estimate the parameter (the same characteristic in the population). In this example, the statistic is **the percent of households headed by single women among the 200 selected households****.**

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