This is typically done in studies where randomization is not possible in order to obtain a representative sample. Bias is more of a concern with this type of sampling. The different types of non-probability sampling are as follows:. The following Slideshare presentation, Sampling in Quantitative and Qualitative Research — A practical how to, offers an overview of sampling methods for quantitative research and contrasts them with qualitative method for further understanding.
Examples of Data Collection Methods — Following is a link to a chart of data collection methods that examines types of data collection, advantages and challenges. Qualitative and Quantitative Data Collection Methods - The link below provides specific example of instruments and methods used to collect quantitative data. Sampling and Measurement - The link below defines sampling and discusses types of probability and nonprobability sampling.
Principles of Sociological Inquiry — Qualitative and Quantitative Methods — The following resources provides a discussion of sampling methods and provides examples. This pin will expire , on Change. This pin never expires. Select an expiration date.
About Us Contact Us. Search Community Search Community. Sampling Methods Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module.
Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each. There are several variations on this type of sampling and following is a list of ways probability sampling may occur: Random sampling — every member has an equal chance Stratified sampling — population divided into subgroups strata and members are randomly selected from each group Systematic sampling — uses a specific system to select members such as every 10 th person on an alphabetized list Cluster random sampling — divides the population into clusters, clusters are randomly selected and all members of the cluster selected are sampled Multi-stage random sampling — a combination of one or more of the above methods Non-probability Sampling — Does not rely on the use of randomization techniques to select members.
The different types of non-probability sampling are as follows: Page Options Share Email Link. Share Facebook Twitter LinkedIn. Pinning this post will make it stay at the top of its channel and widgets. This pin will expire , on Change This pin never expires.
This being the case, purposive sampling is useful to a researcher because they can use the variety of methods available to build and increase their research data. For example, you could start with critical case sampling, and then using the information gathered, progress to expert sampling in stage two.
The main disadvantage of purposive sampling is the high probability of researcher bias, as each sample is based entirely on the judgment of the researcher in question, who generally is trying to prove a specific point. For this reason, researchers need to strive to make decisions based on accepted criteria, not on what will best support their theory. When a researcher publishes their findings, they need to be able to successfully defend their proposal from critics.
Because of the non-probability nature of purposive sampling, it can be more difficult for a researcher to mount a solid defense. The idea behind MVS is to look at a subject from all available angles, thereby achieving a greater understanding. Also known as "Heterogeneous Sampling", it involves selecting candidates across a broad spectrum relating to the topic of study.
This form of sampling, unlike MVS, focuses on candidates who share similar traits or specific characteristics. For example, participants in Homogenous Sampling would be similar in terms of ages, cultures, jobs or life experiences.
The idea is to focus on this precise similarity and how it relates to the topic being researched. For example, if you were researching long-term side effects of working with asbestos, for a Homogenous Sampling, you would only select people who had worked with asbestos for 20 years or longer.
Candidates are generally chosen based on their likelihood of behaving like everyone else. For example, if you were researching the reactions of 9 th grade students to a job placement program, you would select classes from similar socio-economic regions, as opposed to selecting a class from an a poorer inner city school, another from a mid-west farming community, and another from an affluent private school.
The polar opposite of Typical Case Sampling, Extreme or Deviant Case Sampling is designed to focus on individuals that are unusual or atypical. An example would be a study into heart surgery patients who recovered significantly faster or slower than average. Researchers would be looking for variations in these cases to explain why their recoveries were atypical. On occasion, it may be that leaving out certain cases from your sampling would be as if you had an incomplete puzzle - with obvious pieces missing.
In this instance, the best sampling method to use is Total Population Sampling. TPS is a technique where the entire population that meet your criteria e. Total Population Sampling is more commonly used where the number of cases being investigated is relatively small.
As indicated by the name, Expert Sampling calls for experts in a particular field to be the subjects of your purposive sampling.
Purposive sampling (also known as judgment, selective or subjective sampling) is a sampling technique in which researcher relies on his or her own judgment when choosing members of population to participate in the study.
Critical case sampling is a type of purposive sampling technique that is particularly useful in exploratory qualitative research, research with limited resources, as well as research where a single case (or small number of cases) can be decisive in explaining the phenomenon of interest.
Bringing together the work of over eighty leading academics and researchers worldwide to produce the definitive reference and research tool for the social sc. Purposive sampling is using knowledge of the study and the population to choose participants. It is not a random sampling that looks at the whole population. Purposive sampling is also called judgmental sampling and selective sampling. Purposive sampling is essential when researchers are studying a.
Sampling Methods for Quantitative Research. Sampling Methods. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Purposive sampling – members of a particular group are purposefully sought after;. Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation.