Application Assignment Paper: Sampling Components

Sampling components
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Institution of affiliation
Sampling components
Element refers to the subject, event or area under study. According to mathematicians, an element is an algebra of a sample space; therefore, any subject area that is not a subset and is not an element of algebra has no probability. An element in probability is necessary in order to establish accuracy. Upon choosing an appropriate element, it is easier to make relevant probabilities. This is possible because it will be simpler to determine patterns and detect any anomaly in the computation of probability (Hall and Joglar, 2016).
Population in statistics refers to the total set of observations possible. For example, if computing the weight of men, population refers to the total weight of the people in the sample. The population has different ranges that can be used to arrive at probability. Population plays a vital part in sampling and it creates a boundary for the researcher to cover. It gives the area of study, and gives the researcher an idea of what they ought to consider and what to exclude (Kumar, 2014). Appropriate selection of population ensures that the survey is all inclusive. A healthy population should cover most of the characteristics the researcher wants to study to make sure that they do not have gaps in their research. In the example of weight above, the population should capture the weight of men of different ages, in different careers, cities and of different nationalities to find out what are the constant similarities.
A study population in probability refers to a group of elements that have the same characteristics. For example, all A students in Michigan University. The population study paves the way for the researcher to have a sample to review. Therefore, from the study population, the researcher finds a sample. A sample is a smaller group of phenomena selected to represent a particular population. A random sample is selecting the sample without any cons...