Surveying the entire population may not be possible due to the large scale or due to related costs involved in conducting these surveys. Thus, market research deploys sampling techniques to identify the prospective respondents for the research from the total population. There are a lot of different sampling techniques available. These are divided into two main categories based on their approach — probability sampling and non-probability sampling.

Table of Contents It is incumbent on the researcher to clearly define the target population. There are no strict rules to follow, and the researcher must rely on logic and judgment.

The population is defined in keeping with the objectives of the study. Sometimes, the entire population will be sufficiently small, and the researcher can include the entire population in the study.

This type of research is called a census study because data is gathered on every member of the population. Usually, the population is too large for the researcher to attempt to survey all of its members. A small, but carefully chosen sample can be used to represent the population. The sample reflects the characteristics of the population from which it is drawn.

Sampling methods are classified as either probability or nonprobability. In probability samples, each member of the population has a known non-zero probability of being selected.

Probability methods include random sampling, systematic sampling, and stratified sampling. In nonprobability sampling, members are selected from the population in some nonrandom manner. These include convenience sampling, judgment sampling, quota sampling, and snowball sampling.

The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error.

In nonprobability sampling, the degree to which the sample differs from the population remains unknown. Random sampling is the purest form of probability sampling. Each member of the population has an equal and known chance of being selected.

When there are very large populations, it is often difficult or impossible to identify every member of the population, so the pool of available subjects becomes biased. Systematic sampling is often used instead of random sampling.

It is also called an Nth name selection technique. 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.Simple Random Sampling Step 1. Defining the Population Step 2. Constructing a List Step 3. If we do a poor job at the sampling stage of the research process, the integrity of the entire project is How many?

How will they be selected? These are important questions. Each of the sampling techniques described in this chapter has advantages. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Extra care has to be taken to control biases when determining sampling techniques.

There are two main types of sampling: probability and non-probability sampling.

The difference between the two types is whether or not the. 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. 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.

In business and medical research, sampling is widely used for gathering information about a population. Acceptance sampling is used to determine if a production lot of material meets the governing specifications Allows use of different sampling techniques for different subpopulations.

The best and most correct answer among the choices provided by the question is the second choice. All of the following are types of sampling techniques used in research except availability sampling.

I hope my answer has come to your help. God bless and have a nice day ahead!5/5(9).

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Data Sampling Techniques Used in Market Research