﻿ Sampling Error | Definition and Meaning | Capital.com
CFDs are complex instruments and come with a high risk of losing money rapidly due to leverage. 75% of retail investor accounts lose money when trading CFDs with this provider. You should consider whether you understand how CFDs work and whether you can afford to take the high risk of losing your money.
US English

Country Select Country
Entity The products and services listed on this website are not available to US residents.

# What is a sampling error?

A sampling error is a statistical error that occurs when a sample used in a study does not represent the entire population. These errors occur often in the process of sampling which is analysing a selective number of observations from a larger population.

In this article we will learn the sampling error meaning and look at sampling error examples.

A sampling error is the value of difference between the sampled value versus the true or total population value.

It occurs when a subset is taken into consideration instead of the entire set of data. As sampling errors are common, researchers always calculate a margin of error as a practice.

## Types of sampling errors

There are different types of sampling error:

• Population specification error: occurs when the study chooses the wrong set of population. For example, when the study surveys children for an adult product.

• Sample frame error: means that a wrong source of data has been used to derive the sample. For example, when an old phone book that contains limited or outdated information is used as a sample frame for a national survey.

• Selection error: occurs when only participants interested in a survey respond to questions or when the survey is self-selected. Selection errors can be controlled by requesting responses from the entire sample by undertaking follow-ups and pre-survey planning to boost participant response rates.

• Non-response error: happens when participants for a survey are not available or when participants of a survey refuse to respond.

## Examples of sampling error

Let’s consider a research study on children’s footwear as our case study. When buying footwear for a child, parents are typically the decision-makers, but the child may also influence the decision of what to purchase.

In this case, researchers may come across a conundrum on who to survey for the study. It can be only mothers or only fathers, or both parents, or the child. This could lead to a population specification error.

Another example would be a company that sells security cameras and other related home security devices. The firm wants to determine the interest in its higher-priced products and the number of cameras per home.

If the company does not plan its survey carefully, several sampling errors may occur. Selection errors may occur if the company only takes into consideration responses from those who gave their feedback immediately. The company will have to follow-up with unresponsive customers to get the preferences of the entire population.

A population selection error could also occur if it is not understood which customers are the right ones to survey. For example, if the company surveys customers who let their home-building contractors decide which type of security cameras to put and the number of security cameras to deploy, the survey results will be inaccurate.

## Sampling error formula

It’s not difficult to learn how to calculate the sampling error.  Here is a commonly used sampling error formula used in statistical analysis.

Latest video