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Explain in your own words each sampling approach discussed in “Visual Learner: Statistics,” and provide examples of when each technique would be useful.
The Visual Learner Statistics describes five different types of sampling strategies. These are some examples:
Cluster analysis
Cluster Sampling divides the population into sections (clusters), then randomly selects clusters and samples all members of those clusters. Participants can be chosen at random by putting them into groupings such as avenues, schools, and estates. An example of this strategy would be determining the effectiveness of a large city’s police force.In a Simple Random Sample each sample of size n is selected in such a way that every possible sample of size n has the same chance of being selected (Triola 2009). It is based on the theory of probability and usually produce “good” as it is a representative of the population being studied (Johnson & Christensen, p.223). Opinion poll researchers can use random sampling for the people they interview. E.g. Every 10th person passing a street.
Stratified sampling
Under Stratified Sampling the population is subdivided into at least two strata’s that share the same characteristics then acquire samples from both groups.in evaluation of a project without a baseline, the researcher can use the benefitting group and acquire a clone group that never benefitted from the project to compare and establish impacts made (Pennsylvania State University, 2017).
Systematic sampling
Applies when a researcher selects a starting point and samples every nth person. Example can be during the supervision of quality of a road being constructed the Engineer can select every fifth kilometer to acquire sample.
Convenience sampling
This is a method where one uses their judgement and acquires samples that are easy to obtain. Example one may need some questionnaires about bullying in school and therefore collects samples from friends.
References
Johnson, B., & Christensen, L. (2012). Educational Research (Vol. 4). Los Angeles: SAGE Publication.
Pennslavia State University. (2017). STAT 100; Staistical Concepts and Reasoning. Retrieved from STAT 100; Staistical Concepts and Reasoning: https://onlinecourses.science.psu.edu/stat100/node/18
Triola. (2009). Statistics. Retrieved from The Visual Learner: http://lc.gcumedia.com/hlt362v/the-visual-learner/
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