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A stratified sample is one that ensures that subgroups (strata) of a given population are each adequately represented within the whole sample population of a research study. For example, one might divide a sample of adults into subgroups by age, like 18-29, 30-39, 40-49, 50-59, and 60 and above.
https://www.thoughtco.com/stratified-sampling-3026731

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Quota Sampling is a non-probability sampling method in which researchers can form a sample involving individuals that represent a population and are chosen according to traits or qualities. Researchers can decide the trait as per which the sample subset selection will be conducted so that the sample can be effective in collecting data that can be generalized to the entire population. The final subset will be decided only according to the interviewer or researcher’s knowledge of the population.

https://www.questionpro.com/blog/quota-sampling/

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Snowball sampling is where research participants recruit other participants for a test or study. It is used where potential participants are hard to find. It’s called snowball sampling because (in theory) once you have the ball rolling, it picks up more “snow” along the way and becomes larger and larger. Snowball sampling is a non-probability sampling method. It doesn’t have the probability involved, with say, simple random sampling(where the odds are the same for any particular participant being chosen). Rather, the researchers used their own judgment to choose participants.

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Also known as selective, or subjective, sampling, this technique relies on the judgement of the researcher when choosing who to ask to participate. Researchers may implicitly thus choose a “representative” sample to suit their needs, or specifically approach individuals with certain characteristics. This approach is often used by the media when canvassing the public for opinions and in qualitative research.

Judgement sampling has the advantage of being time-and cost-effective to perform whilst resulting in a range of responses (particularly useful in qualitative research). However, in addition to volunteer bias, it is also prone to errors of judgement by the researcher and the findings, whilst being potentially broad, will not necessarily be representative.
https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population

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method of choosing a random sample from among a larger population. The process of systematic sampling typically involves first selecting a fixed starting point in the larger population and then obtaining subsequent observations by using a constant interval between samples taken.
http://www.businessdictionary.com/definition/systematic-sampling.html

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Snowball sampling

Snowball sampling (also known as chain-referral sampling) is a non-probability (non-random) sampling method used when characteristics to be possessed by samples are rare and difficult to find. For example, if you are studying the level of customer satisfaction among elite Nirvana Bali Golf Club in Bali, you will find it increasingly difficult to find primary data sources unless a member is willing to provide you with contacts of other members.

This sampling method involves primary data sources nominating another potential primary data sources to be used in the research. In other words, snowball sampling method is based on referrals from initial subjects to generate additional subjects. Therefore, when applying this sampling method members of the sample group are recruited via chain referral.

https://research-methodology.net/sampling-in-primary-data-collection/snowball-sampling/

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judgmental sampling or authoritative sampling, is a non-probability sampling technique where the researcher selects units to be sampled based on his own existing knowledge, or his professional judgment.

As a refresher, non-probability sampling is where the samples for a study are gathered in a process that does not give all of the individuals in the population equal chances of being selected.

https://www.surveygizmo.com/resources/blog/introduction-to-judgment-sampling/

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What is Systematic SamplingSystematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. Despite the sample population being selected in advance, systematic sampling is still thought of as being random if the periodic interval is determined beforehand and the starting point is random.

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What is Systematic SamplingSystematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. Despite the sample population being selected in advance, systematic sampling is still thought of as being random if the periodic interval is determined beforehand and the starting point is random.

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https://www.investopedia.com/terms/s/systematic-sampling.asp

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Non-random or non-probability sampling refers to sampling methods that do not adhere to the principles ofprobability sampling, i.e. that not everyone in the population has an equal chance of being selected. For this reason, non-random sampling is not used very often in quantitativehealth and social care research.
https://www.google.com/url?sa=t&source=web&rct=j&url=https://www.researchgate.net/file.PostFileLoader.html%3Fid%3D52bdb167d2fd641f2b8b45ec%26assetKey%3DAS%253A272429845286951%25401441963744867&ved=2ahUKEwjMiOXYtZDhAhWVQhUIHWB9DbgQFjABegQIDhAE&usg=AOvVaw3WmeyFXC7tm3o19gDEWzos

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A convenience sample is a non-probability sample in which the researcher uses the subjects that are nearest and available to participate in the research study. This technique is also referred to as "accidental sampling," and is commonly used in pilot studies prior to launching a larger research project.
https://www.thoughtco.com/convenience-sampling-3026726

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Quota sampling method is a non-probability sampling and it can be defined as a sampling method of gathering representative data from a group. Application of quota sampling ensures that sample group represents certain characteristics of the population chosen by the researcher.

Quota sampling can be divided into two groups: controlled and uncontrolled.

Controlled quota sampling involves introduction of certain restrictions in order to limit researcher’s choice of samples.

Uncontrolled quota sampling, on the other hand, resembles convenience sampling method in a way that researcher is free to choose sample group members according to his/her will.

The main difference between quota and stratified sampling can be explained in a way that in quota sampling researchers use non-random sampling methods to gather data from one stratum until the required quota fixed by the researcher is fulfilled. Accordingly, the quota is based on the proportion of subclasses in the population
https://research-methodology.net/sampling-in-primary-data-collection/quota-sampling/

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With cluster sampling, the researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters.

cluster sampling has advantages and disadvantages. For example, given equal sample sizes, cluster sampling usually provides less precision than either simple random sampling or stratified sampling. On the other hand, if travel costs between clusters are high, cluster sampling may be more cost-effective than the other methods.

https://stattrek.com/statistics/dictionary.aspx?definition=cluster_sampling

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This method is commonly used in social sciences when investigating hard-to-reach groups. Existing subjects are asked to nominate further subjects known to them, so the sample increases in size like a rolling snowball. For example, when carrying out a survey of risk behaviours amongst intravenous drug users, participants may be asked to nominate other users to be interviewed.

Snowball sampling can be effective when a sampling frame is difficult to identify. However, by selecting friends and acquaintances of subjects already investigated, there is a significant risk of selection bias (choosing a large number of people with similar characteristics or views to the initial individual identified).

https://www.healthknowledge.org.uk/public-health-textbook/research-methods/1a-epidemiology/methods-of-sampling-population

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Snowball sampling is a commonly employed sampling method in qualitative research; however, the diversity of samples generated via this method has repeatedly been questioned. Scholars have posited several anecdotally based recommendations for enhancing the diversity of snowball samples. In this study, we performed the first quantitative, medium-N analysis of snowball sampling to identify pathways to sample diversity, analysing 211 reach-outs conducted via snowball sampling, resulting in 81 interviews; these interviews were administered between April and August 2015 for a research project on anti-dam movements in Southeast Asia. Based upon this analysis, we were able to refine and enhance the previous recommendations (e.g., showcasing novel evidence on the value of multiple seeds or face-to-face interviews). This paper may thus be of particular interest to scholars employing or intending to employ snowball sampling.
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0201710

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quota sampling

A sampling method of gathering representative data from a group. As opposed to random sampling, quota sampling requires that representative individuals are chosen out of a specific subgroup. For example, a researcher might ask for a sample of 100 females, or 100 individuals between the ages of 20-30.

http://www.businessdictionary.com/definition/quota-sampling.html

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Stratified random sampling is a type of probability sampling using which a research organization can branch off the entire population into multiple non-overlapping, homogeneous groups (strata) and randomly choose final members from the various strata for research which reduces cost and improves efficiency.

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Stratified random sampling is a type of probability sampling using which a research organization can branch off the entire population into multiple non-overlapping, homogeneous groups (strata) and randomly choose final members from the various strata for research which reduces cost and improves efficiency.

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https://www.questionpro.com/blog/stratified-random-sampling/

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A convenience sample is one of the main types of non-probability sampling methods. A convenience sample is made up of people who are easy to reach.

Consider the following example. A pollster interviews shoppers at a local mall. If the mall was chosen because it was a convenient site from which to solicit survey participants and/or because it was close to the pollster's home or business, this would be a convenience sample.

https://stattrek.com/statistics/dictionary.aspx?definition=cluster_sampling

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Convenience sampling is a non-probability sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher.

https://explorable.com/convenience-sampling

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Simple random sampling is a sampling technique where every item in the population has an even chance and likelihood of being selected in the sample. Here the selection of items completely depends on chance or by probability and therefore this sampling technique is also sometimes known as a method of chances. 

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Simple random sampling is a sampling technique where every item in the population has an even chance and likelihood of being selected in the sample. Here the selection of items completely depends on chance or by probability and therefore this sampling technique is also sometimes known as a method of chances. 

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Simple random sampling is a very basic type of sampling method and can easily be a component of a more complex sampling method. The main attribute of this sampling method is that every sample has the same probability of being chosen.
https://www.questionpro.com/blog/simple-random-sampling/

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In most cases, some type of "judgment sample" is used to collect data from a system. Unfortunately, judgment sampling is not well understood. ... The purpose of this article is to describe judgment sampling and its importance in quality improvement work and studies with a focus onhealth care settings.
https://www.ncbi.nlm.nih.gov/m/pubmed/22722523/

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Cluster Sampling

Cluster sampling refers to a type of sampling method . With cluster sampling, the researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters.

https://stattrek.com/statistics/dictionary.aspx?definition=cluster_sampling

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Quota sampling: This is a non-random form of sampling and is often used when there is little time to recruit people for a study. First researchers identify important characteristics that they want their sample to contain. Then researchers set out to recruit certain numbers of participants with these characteristics.
https://www.understandinghealthresearch.org/useful-information/sampling-methods-1

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Stratified sampling is used to select a sample that is representative of different groups. If the groups are of different sizes, the number of items selected from each group will be proportional to the number of items in that group.

https://www.bbc.com/bitesize/guides/zy9frwx/revision/3

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Simple random sampling (also referred to as random sampling) is the purest and the most straightforward probability sampling strategy. It is also the most popular method for choosing a sample among population for a wide range of purposes. In simple random sampling each member of population is equally likely to be chosen as part of the sample. It has been stated that “the logic behind simple random sampling is that it removes bias from the selection procedure and should result in representative samples”[1].

https://research-methodology.net/sampling-in-primary-data-collection/random-sampling/

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Simple random sampling is a type of probability sampling technique [see our article, Probability sampling, if you do not know what probability sampling is]. With the simple random sample, there is an equal chance (probability) of selecting each unit from the population being studied when creating your sample [see our article, Sampling: The basics, if you are unsure about the terms unit, sample and population]. This article (a) explains what simple random sampling is, (b) how to create a simple random sample, and (c) the advantages and disadvantages of simple random sampling.
http://dissertation.laerd.com/simple-random-sampling.php

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Snowball sampling."Snowball sampling" refers to a non-probability sampling technique in which a researcher begins with a small population of known individuals and expands the sample by asking those initial participants to identify others that should participate in the study. In other words, the sample starts small but "snowballs" into a larger sample through the course of the research.it is a very good technique for conducting exploratory research and/or qualitative research with a specific and relatively small population that is hard to identify or locate.https://www.thoughtco.com/snowball-sampling-3026730 

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Snowball sampling."Snowball sampling" refers to a non-probability sampling technique in which a researcher begins with a small population of known individuals and expands the sample by asking those initial participants to identify others that should participate in the study. In other words, the sample starts small but "snowballs" into a larger sample through the course of the research.it is a very good technique for conducting exploratory research and/or qualitative research with a specific and relatively small population that is hard to identify or locate.https://www.thoughtco.com/snowball-sampling-3026730 

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Convenience sampling is a type of sampling where the first available primary data source will be used for the research without additional requirements. In other words, this sampling method involves getting participants wherever you can find them and typically wherever is convenient. In convenience sampling no inclusion criteria identified prior to the selection of subjects.  All subjects are invited to participate.
https://research-methodology.net/sampling-in-primary-data-collection/convenience-sampling/

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Cluster sampling refers to a type of  sampling method . With cluster sampling, the researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters.

Compared to  simple random sampling and  stratified sampling , cluster sampling has advantages and disadvantages. For example, given equal sample sizes, cluster sampling usually provides less precision than either simple random sampling or stratified sampling. On the other hand, if travel costs between clusters are high, cluster sampling may be more cost-effective than the other methods.

https://stattrek.com/statistics/dictionary.aspx?definition=cluster_sampling

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What is Systematic Sampling

Systematic sampling is a type of probability sampling method in which sample members from a larger population are selected according to a random starting point and a fixed, periodic interval. This interval, called the sampling interval, is calculated by dividing the population size by the desired sample size. Despite the sample population being selected in advance, systematic sampling is still thought of as being random if the periodic interval is determined beforehand and the starting point is random.

For example, if you wanted to select a random group of 1,000 people from a population of 50,000 using systematic sampling, all the potential participants must be placed in a list and a starting point would be selected. Once the list is formed, every 50th person on the list (starting the count at the selected starting point) would be chosen as a participant, since 50,000/1,000 = 50. For example, if the selected starting point was 20, the 70th person on the list would be chosen followed by the 120th, and so on. Once the end of the list was reached and if additional participants are required, the count loops to the beginning of the list to finish the count.

https://www.investopedia.com/terms/s/systematic-sampling.asp

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Clustered sampling is referred as a sampling method. This is where the individual doing the research shall divide the population into separate groups called clusters. The a random group of clusters will be selected and the researcher will analyse the data from that certain cluster (group of certain participants)

The advantage is: gives equal sample sizes.

The disadvantages are that: one of the most cost-effective than other methods  and uses less precision.

https://stattrek.com/statistics/dictionary.aspx?d

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What Is a Simple Random Sample?

A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group.

An example of a simple random sample would be the names of 25 employees being chosen out of a hat from a company of 250 employees. In this case, the population is all 250 employees, and the sample is random because each employee has an equal chance of being chosen. Random sampling is used in science to conduct randomized control tests or for blinded experiments.

https://www.investopedia.com/terms/s/simple-random-sample.asp

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A sampling method of gathering representative data from a group. As opposed to random sampling, quota sampling requires that representative individuals are chosen out of a specific subgroup. For example, a researcher might ask for a sample of 100 females, or 100 individuals between the ages of 20-30

http://www.businessdictionary.com/definition/quota-sampling.html