File Name: non probability sampling advantages and disadvantages .zip
Home QuestionPro Products Audience. Definition: Non-probability sampling is defined as a sampling technique in which the researcher selects samples based on the subjective judgment of the researcher rather than random selection. It is a less stringent method.
When to use it. Ensures a high degree of representativeness, and no need to use a table of random numbers. When the population is heterogeneous and contains several different groups, some of which are related to the topic of the study. Ensures a high degree of representativeness of all the strata or layers in the population. Possibly, members of units are different from one another, decreasing the techniques effectiveness.
Reducing sampling error is the major goal of any selection technique. A sample should be big enough to answer the research question, but not so big that the process of sampling becomes uneconomical. Estimating sample size — in general, you need a larger sample to accurately represent the population when:. The amount of variability within groups is greater, and. The difference between the tw groups gets smaller. In general, the larger the sample, the smaller the sampling error and the better job you can do.
If you are going to use several subgroups in your work such as males and females who are both 10 years of age, and healthy and unhealthy urban residents , be sure your initial selection of subjects is large enough to account for the eventual breaking down of subject groups.
Remember that big is good, but appropriate is better. Do not waste your hard-earned money or valuable time generating samples that are larger than you need… law of diminishing returns will set in! Estimating sample size — in general, you need a larger sample to accurately represent the population when: a. The amount of variability within groups is greater, and b. Type of Sampling. Probability Strategies. Simple Random Sampling. When the population members are similar to one another on important variables.
Ensures a high degree of representativeness. Time consuming and tedious. Systematic Sampling. Less random than simple random sampling. Stratified Random Sampling. Cluster Sampling. When the population consists of units rather than individuals. Easy and convenient. Non-Probability Sampling.
Convenience Sampling. When the members of the population are convenient to sample. Convenience and inexpensive. Degree of generalizability is questionable. Quota Sampling. When strata are present and stratified sampling is not possible. Insures some degree of representativeness of all the strata in the population.
The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling does. Not necessarily. But it does mean that nonprobability samples cannot depend upon the rationale of probability theory. At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. In general, researchers prefer probabilistic or random sampling methods over nonprobabilistic ones, and consider them to be more accurate and rigorous.
When to use it. Ensures a high degree of representativeness, and no need to use a table of random numbers. When the population is heterogeneous and contains several different groups, some of which are related to the topic of the study.
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It would normally be impractical to study a whole population, for example when doing a questionnaire survey. Sampling is a method that allows researchers to infer information about a population based on results from a subset of the population, without having to investigate every individual. Reducing the number of individuals in a study reduces the cost and workload, and may make it easier to obtain high quality information, but this has to be balanced against having a large enough sample size with enough power to detect a true association. Calculation of sample size is addressed in section 1B statistics of the Part A syllabus. If a sample is to be used, by whatever method it is chosen, it is important that the individuals selected are representative of the whole population.
By Dr. Saul McLeod , updated In psychological research we are interested in learning about large groups of people who all have something in common. We call the group that we are interested in studying our 'target population'.
Probability and non-probability sampling have advantages and disadvantages and the use of each is determined by the researcher's goals in relation to data.Lodelere 13.05.2021 at 05:54
We use Sampling techniques to reduce the time, money and other resources to be invested for our survey.Holly E. 18.05.2021 at 03:52
Convenience sampling also known as grab sampling , accidental sampling , or opportunity sampling is a type of non-probability sampling that involves the sample being drawn from that part of the population that is close to hand.