Number of elements in the sample is the sample size.
The difference lies between the above two is whether the sample selection is based on randomization or not.
Population is divided into multiple clusters and then these clusters are further divided and grouped into various sub groups (strata) based on similarity.
One or more clusters can be randomly selected from each stratum.
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Contact us if you experience any difficulty logging in.We select our first element randomly from the first subgroup of k elements.To select other elements of sample, perform following: We know number of elements in each group is k i.e N/n So if our first element is n1 then Second element is n1 k i.e n2Third element n2 k i.e n3 and so on..There are lot of techniques which help us to gather sample depending upon the need and situation.This blog post tries to explain some of those techniques.The sampling strategy that you select in your dissertation should naturally flow from your chosen research design and research methods, as well as taking into account issues of research ethics.To set the sampling strategy that you will use in your dissertation, you need to follow three steps: (a) understand the key terms and basic principles; (b) determine which sampling technique you will use to select the units that will make up your sample; and (c) consider the practicalities of choosing such a sampling strategy for your dissertation (e.g., what time you have available, what access you have, etc.).Cluster Sampling Our entire population is divided into clusters or sections and then the clusters are randomly selected.All the elements of the cluster are used for sampling.In Sampling: The basics, we including terms such as units/cases/objects, sample, sampling frame, population, sample size, random sampling, sampling bias, amongst other terms.If you are already confident that you understand these basic principles of sampling, we introduce you to the two major groups of sampling techniques that you could use to select the units that you will include in your sample: We explain what each of these types of sampling technique are, how to create them, and their advantages and disadvantages.