The assumption of an equal chance of selection means that sources such as a telephone book or voter registration lists are not adequate for providing a random sample of a community. In both these cases there will be a number of residents whose names are not listed.
Telephone surveys get around this problem by random-digit dialing -- but that assumes that everyone in the population has a telephone. The key to random selection is that there is no bias involved in the selection of the sample.
Any variation between the sample characteristics and the population characteristics is only a matter of chance. A stratified sample is a mini-reproduction of the population. Before sampling, the population is divided into characteristics of importance for the research.
For example, by gender, social class, education level, religion, etc. Then the population is randomly sampled within each category or stratum. How to Construct a probability representative sample. As they are not truly representative, non-probability samples are less desirable than probability samples.
However, a researcher may not be able to obtain a random or stratified sample, or it may be too expensive. A researcher may not care about generalizing to a larger population. The validity of non-probability samples can be increased by trying to approximate random selection, and by eliminating as many sources of bias as possible.
A researcher is interested in the attitudes of members of different religions towards the death penalty. In Iowa a random sample might miss Muslims because there are not many in that state. It is important to understand that the saturation point may occur prematurely if the researcher has a narrow sampling frame, a skewed analysis of the data, or poor methodology.
Because of this, the researcher must carefully create the research question, select an appropriate target group, eliminate his or her own biases and analyze data continuously and thoroughly throughout the process to bring validity to the data collected. The following slideshare presentation, Collecting Qualitative Data , and the Resource Links on this page provide additional insight into qualitative sampling.
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. Qualitative Research Overview - The following link provides a full overview of qualitative research, but also contains sections discussing types of sampling methods and methods of participant recruitment. Sampling - This resource provides a brief overview of sampling and sample size with links to descriptions of purposeful sampling strategies.
A Guide to Using Qualitative Research Methodology - The file linked below contains a full description of how to conduct qualitative sampling, including a chart that lists the types of sampling techniques and includes examples. Sampling Designs in Qualitative Research - The following article discusses sampling designs and ways to make the sampling process more public. This pin will expire , on Change. This pin never expires.
Select an expiration date. About Us Contact Us. Search Community Search Community. Qualitative Sampling Methods The following module describes common methods for collecting qualitative data. Describe common types of qualitative sampling methodology. Explain the methods typically used in qualitative data collection. Describe how sample size is determined. A stratum is a subset of the population that share at least one common characteristic. Examples of stratums might be males and females, or managers and non-managers.
The researcher first identifies the relevant stratums and their actual representation in the population. Random sampling is then used to select a sufficient number of subjects from each stratum. Stratified sampling is often used when one or more of the stratums in the population have a low incidence relative to the other stratums.
Convenience sampling is used in exploratory research where the researcher is interested in getting an inexpensive approximation of the truth. As the name implies, the sample is selected because they are convenient. This nonprobability method is often used during preliminary research efforts to get a gross estimate of the results, without incurring the cost or time required to select a random sample.
Judgment sampling is a common nonprobability method. The researcher selects the sample based on judgment. This is usually and extension of convenience sampling. For example, a researcher may decide to draw the entire sample from one "representative" city, even though the population includes all cities.
When using this method, the researcher must be confident that the chosen sample is truly representative of the entire population. Quota sampling is the nonprobability equivalent of stratified sampling. Like stratified sampling, the researcher first identifies the stratums and their proportions as they are represented in the population. Then convenience or judgment sampling is used to select the required number of subjects from each stratum.
Sampling Methods. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives.
Video: What is Sampling in Research? - Definition, Methods & Importance - Definition, Methods & Importance The sample of a study can have a profound impact on the outcome of a study.
There are many methods of sampling when doing research. This guide can help you choose which method to use. Simple random sampling is the ideal, but researchers seldom have the luxury of time or money to access the whole population, so many compromises often have to be made. This was a presentation that was carried out in our research method class by our group. It will be useful for PHD and master students quantitative and qualitat.