The sample size may be predetermined or based on theoretical saturation, which is the point at which the newly collected no longer provides additional insights. Click on the following link for a desciption of types of purposeful sampling: Types of Purposeful Sampling. Quota Sampling is a sampling technique whereby participant quotas are preset prior to sampling.
Typically, the researcher is attempting to gather data from a certain number of participants that meet certain characteristics that may include things such as age, sex, class, marital status, HIV status, etc. Click here for more information on this type of sampling: Snowball Sampling is also known as chain referral sampling.
In this method, the participants refer the researcher to others who may be able to potentially contribute or participate in the study. This method often helps researchers find and recruit participants that may otherwise be hard to reach.
For more information, click here: Collecting Qualitative Data from highness Qualitative Sampling Methods by ProProfs. Resource Links Qualitative Research Methods - A Data Collectors Field Guide - This comprehensive, detailed guide describes various types of sampling techniques and provides examples of each, as well as pros and cons. 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. In particular when you are studying a number of groups and when sub-groups are small, then you will need equivalent numbers to enable equivalent analysis and conclusions.
Good sampling is time-consuming and expensive. Not all experimenters have the time or funds to use more accurate methods. There is a price, of course, in the potential limited validity of results. When doing field-based observations, it is often impossible to intrude into the lives of people you are studying. Samples must thus be surreptitious and may be based more on who is available and willing to participate in any interviews or studies.
Please help and share: Method Best when Simple random sampling Whole population is available. Stratified sampling random within target groups There are specific sub-groups to investigate eg. Systematic sampling every nth person When a stream of representative people are available eg. Cluster sampling all in limited groups When population groups are separated and access to all is difficult, eg.
Method Best when Quota sampling get only as many as you need You have access to a wide population, including sub-groups Proportionate quota sampling in proportion to population sub-groups You know the population distribution across groups, and when normal sampling may not give enough in minority groups Non-proportionate quota sampling minimum number from each sub-group There is likely to a wide variation in the studied characteristic within minority groups.
Let's say that you are conducting research related to a fruit market. What will be studied in the fruit market? Is it a type of fruit or the fruit sellers themselves? Let's say you identify citrus fruit as the unit of analysis, and your population is all citrus fruit within the Bauchi Road fruit market.
There are too many pieces of citrus fruit for you to study in that market, so you must select only a sample of the citrus fruit. A common error in sampling is that the sample and population are not identical. For example, the sample may be too narrow. If the population is all citrus fruit within the Bauchi Road fruit market, then the sample cannot only consist of lemons because your sample would be missing oranges, grapefruit, and limes. Therefore, you must find a way of selecting a representative sample of citrus fruit from your population.
To apply to an educational study, perhaps one may say that the population is all university students, but only university students in public schools are sampled. Another common error is to make the population too broad. Some may say that the population is all mangoes in the Bauchi Road fruit market, but they are really only interested in green mangoes.
If only green mangoes are of interest, then the population should be green mangoes in the Bauchi Road fruit market. In educational research, sometimes researchers are only interested in a population with a certain characteristic, such as student who has not chosen a career in the case of career counseling. Thus, the population and sample must be the same.
Before selecting a sampling procedure, first consider the following: Select the unit of analysis. When selecting the sample, it is imperative that the sampling technique selects cases based on this unit of analysis. In other words, if the unit of analysis is students, then the sampling technique must focus solely on how the students were selected. It would be an error to describe the selection of schools as the sampling technique when the unit of analysis is students.
Determine how many units need to be sampled. This step is a tricky balancing act. On the one hand, larger samples tend to be more representative of the target population and provide stronger statistical power. On the other hand, larger samples can decrease the quality of the research study, particularly for experimental and quasi-experimental designs.
In experimental designs, if many people participate in the treatment, then the quality of treatment that each individual receives might suffer, resulting in inaccurate conclusions. It is a truism that overpopulation in classrooms reduces the impact of instruction; if there are too many students in the class, then the teaching will not be as effective.
Likewise, we should equally avoid the problem of overpopulation in experiments: Therefore, smaller treatment groups are generally preferable. In general, descriptive designs require at least participants, correlational designs require at least 30 participants, and experimental, quasi-experimental, and causal-comparative designs require at least 15 participants per group.
The size of the sample in experiments depend on how effective the treatment is. If you have a very effective treatment, then only a few participants are necessary.
However, if the treatment is weak, then a larger sample size is necessary to find a significant effect. There are many sampling procedures that have been developed to ensure that a sample adequately represents the target population.
Because sampling isn't as straightforward as it initially seems, there is a set process to help researchers choose a good sample. Let's look closer at the process and importance of sampling. Process. So Brooke wants to choose a group of college students to take part in her study. To select her sample, she goes through the basic steps of sampling. 1.
RESEARCH METHOD - SAMPLING 1. Quota sampling the process whereby a researcher gathers data from individuals possessing identified characteristics and quotas who are less accessible (more difficult to contact, more reluctant to participate) are under-represented Sampling in Qualitative Research .
Sampling is the process of selecting units (e.g., people, organizations) from a population of interest so that by studying the sample we may fairly generalize our results back to . The goal of qualitative research is to provide in-depth understanding and therefore, targets a specific group, type of individual, event or process. To accomplish this goal, qualitative research focus on criterion-based sampling techniques to reach their target group.
Snowball sampling – members are sampled and then asked to help identify other members to sample and this process continues until enough samples are collected The following Slideshare presentation, Sampling in Quantitative and Qualitative Research – A practical how to, offers an overview of sampling methods for quantitative research and. The steps in the research process are, identification and definition of the problem or opportunity, planning the research design, selecting a research method, selecting a sampling procedure, data collection, evaluating the data and finally preparing and presenting the research report. Identifying 5/5(8).