Different Sampling Methods

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Learning Team A Week Five Reflection

In week four of class, one of the objectives that Team A covered in discussions was how to develop collection instruments. These instruments can be used to extract, assess, monitor, and record data and information. This process is important to ensure that all accurate needed information is gathered to make fact based changes to present procedures. The second objective we learned was how to differentiate between sampling methods and to apply their application in business research. The different sampling methods include simple random, systematic, stratified, cluster, convenience, judgment, quota, and snowball. These techniques can be of use to gather information about the way different variables affect large or small populations of individuals. This paper is a reflection on the concepts Team A learned in week four of class. A Census on the other hand will be used when the population is small and when there is a big difference in the answer, For example "Some companies specialize in speakers, some in amplifier technology, and others in compact-disc transports" (Axia College RES/351 Ch 14 p. 365). These are some examples of when a census would be used. Accuracy is when the sample was drawn correctly to its conclusion. For example getting almost all the surveys back compared to half. Precision, or known as random sampling error, is done upon what the surveys suggest against what their system might have calculated. The closer the surveys are to the system data, the closer the precision. A researcher has multiple sampling methods available to choose from when performing research. The different sampling methods available are simple random, systematic, stratified, cluster, convenience, judgment, quota, and snowball sampling. Simple random sampling is a simple percentage randomly selected from the target population.  An example could be if ABC Widget Company mailed a product questionnaire to 1000 random customers taken from a...
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