## What Is Snowball Sampling? | Definition & Examples

Snowball sampling is a non-probability sampling method where new units are recruited by other units to form part of the sample. Snowball sampling can be a useful way to conduct research about people with specific traits who might otherwise be difficult to identify (e.g., people with a rare disease).

Also known as chain sampling or network sampling, snowball sampling begins with one or more study participants. It then continues on the basis of referrals from those participants. This process continues until you reach the desired sample, or a saturation point.

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## What Is Quota Sampling? | Definition & Examples

Quota sampling is a non-probability sampling method that relies on the non-random selection of a predetermined number or proportion of units. This is called a quota.

You first divide the population into mutually exclusive subgroups (called strata) and then recruit sample units until you reach your quota. These units share specific characteristics, determined by you prior to forming your strata.

The aim of quota sampling is to control what or who makes up your sample. Your design may:

• Replicate the true composition of the population of interest
• Include equal numbers of different types of respondents
• Over-sample a particular type of respondent, even if population proportions differ

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## What Is Purposive Sampling? | Definition & Examples

Purposive sampling refers to a group of non-probability sampling techniques in which units are selected because they have characteristics that you need in your sample. In other words, units are selected ‘on purpose’ in purposive sampling.

Also called judgemental sampling, this sampling method relies on the researcher’s judgement when identifying and selecting the individuals, cases, or events that can provide the best information to achieve the study’s objectives.

Purposive sampling is common in qualitative research and mixed methods research. It is particularly useful if you need to find information-rich cases or make the most out of limited resources.

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## What Is Convenience Sampling? | Definition & Examples

Convenience sampling is a non-probability sampling method where units are selected for inclusion in the sample because they are the easiest for the researcher to access.

This can be due to geographical proximity, availability at a given time, or willingness to participate in the research. Sometimes called accidental sampling, convenience sampling is a type of non-random sampling.

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## What Is Non-Probability Sampling? | Types & Examples

Non-probability sampling is a sampling method that uses non-random criteria like the availability, geographical proximity, or expert knowledge of the individuals you want to research in order to answer a research question.

Non-probability sampling is used when the population parameters are either unknown or not possible to individually identify. For example, visitors to a website that doesn’t require users to create an account could form part of a non-probability sample.

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## What Is Probability Sampling? | Types & Examples

Probability sampling is a sampling method that involves randomly selecting a sample, or a part of the population that you want to research. It is also sometimes called random sampling.

To qualify as being random, each research unit (e.g., person, business, or organisation in your population) must have an equal chance of being selected. This is usually done through a random selection process, like a drawing, to minimise the risk of selection bias.

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## What Is Social Desirability Bias? | Definition & Examples

Social desirability bias occurs when respondents give answers to questions that they believe will make them look good to others, concealing their true opinions or experiences. This type of research bias often affects studies that focus on sensitive or personal topics, such as politics, drug use, or sexual behaviour.

Social desirability bias is a type of response bias. Here, study participants have a tendency to answer questions in such a way as to present themselves in socially acceptable terms, or in an attempt to gain the approval of others.

It is especially likely to occur in self-report questionnaires, but it can also affect the validity of any type of behavioural research, particularly if the participants know they’re being observed.

The risk of researchers or respondents influencing (biasing) a study and its results, whether consciously or unconsciously, is inherent to conducting human-centred research. However, there are ways to detect and reduce bias in your research design if you know what to look for.

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