For a particular analysis and valid results, you can determine the number of people you need to sample. 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.
Method Best when Purposive sampling based on intent You are studying particular groups Expert sampling seeking 'experts' You want expert opinion Snowball sampling ask for recommendations You seek similar subjects eg. Method Best when Snowball sampling ask for recommendations You are ethically and socially able to ask and seek similar subjects. Convenience sampling use who's available You cannot proactively seek out subjects.
Judgment sampling guess a good-enough sample You are expert and there is no other choice. Method Best when Selective sampling gut feel Focus is needed in particular group, location, subject, etc. After the required sample size has been calculated, every Nth record is selected from a list of population members.
As long as the list does not contain any hidden order, this sampling method is as good as the random sampling method. Its only advantage over the random sampling technique is simplicity. Systematic sampling is frequently used to select a specified number of records from a computer file. Stratified sampling is commonly used probability method that is superior to random sampling because it reduces sampling error. 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. This differs from stratified sampling, where the stratums are filled by random sampling. Snowball sampling is a special nonprobability method used when the desired sample characteristic is rare.
It may be extremely difficult or cost prohibitive to locate respondents in these situations.
Sampling Methods. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each.
Convenience methods. Good sampling is time-consuming and expensive. Not all experimenters have the time or funds to use more accurate methods. There is a .
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 . RESEARCH METHOD - SAMPLING 1. Sampling Techniques & Samples Types 2. Outlines Sample definition Purpose of sampling Stages in the selection of a sample Types of sampling in quantitative researches Types of sampling in qualitative researches Ethical Considerations in Data Collection 3.
Once you know your population, sampling frame, sampling method, and sample size, you can use all that information to choose your sample. Importance As you can . Another excellent source of public opinion polls on a wide variety of topics using solid sampling methodology is the Pew Research Center website at donnievales9rdq.cf When you read one of the summary reports on the Pew site, there is a link (in the upper right corner).