Please discuss the conventions pertaining to sampling designs and sampling proce
ID: 332941 • Letter: P
Question
Please discuss the conventions pertaining to sampling designs and sampling procedures. If you wished to find out the percentage of customers of the local Post Office who purchased postage stamps on a given day, would you perform a sample? Probably not. If you wished to find out the same percentage over a one year period, you would probably use a sampling technique. Why? Choose at least two other procedures and discuss the need for sampling. Please also discuss relevant populations in sampling, random sampling, sampling error, and probability sampling in this discussion
Explanation / Answer
Sampling is described as a process in which a sample is elected from an individual or a group of people for research purpose. Information about the distinctiveness of a population may be acquired through efficient and effective sampling designs where information’s pertaining to time constraints, population size, variations etc are taken into consideration.
Thus sampling procedure is instigated by signifying the target population in terms of elements, sampling units, extent and time then an overall sampling structure is indeed required to establish the representation of the fundamental elements of the target population.
Thus it consists of a list of directions for categorizing the target population furthermore it’s very crucial to identify any kind sampling structure errors that may subsist then it’s important to choose a sampling technique and establish the sample size by taking into consideration the quantitative and qualitative analysis and lastly the implementation of the sampling process necessitates a comprehensive stipulations for each step in the sampling process.
Thus sampling do facilitates in ensuring expediency, compilation of exhaustive and wide-ranging data, appropriateness in restricted resources and enhanced understanding. Furthermore after having drawn a sample and calculated the desired explanatory statistics then it becomes feasible to establish the steadiness of the acquired sample value.
Random sampling refers to a subset of a statistical population in which each element of the subset has an equivalent possibility of being selected. For instance 25 workers selected from a total 250 workers in an organization thus in this case the population is all 250 workers and the sample is random as each worker has an equivalent probability of getting selected.
Sampling error is sustained when the statistical characteristics of a population are anticipated from a subset or sample of that population. Since the illustration does not comprise all components of the population information on the sample such as means and quintiles normally varies from the uniqueness and distinctiveness of the whole population known as parameters.
In probability sampling every element in the population has a probability (greater than zero) of being elected in the sample and this possibility can be precisely and perfectly determined. Thus the arrangement of these characters makes it probable to create an impartial approximation of population total by weighing sampled components as per their possibility of assortment.