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Data quality

There are certain necessary attributes in determining the quality of data for an analysis process. Since the values and measurements of data will all affect the analysis procedure, it should always be considered to acquire the most appropriate values for the intentional goal of describing a set of population under study (Wikipedia, 2007). There are some procedures that can help in identifying whether a set of data is of high standards. First, the user or the researcher should be able to see whether the given set of raw information was gathered in a sampling technique according to the research design.

For example, a sampling procedure based on statistical formulation can be used. Next, the raw data should at least be acquired from the target population of interest. This will somehow provide a greater picture of the behavior of the components being observed. Thirdly, the collected data should represent a complete set of parameters of interest for analysis. All other information about each observation in the data should have the necessary information to support the major data values.

In order to ensure the quality of data upon retrieving it, the best practice is to maintain the original component of the information. Although it is always necessary to alter the mechanism according to the researcher’s purpose, one should always make it a point to implement the original goal of the analysis. In this aspect, the design principle of the research will definitely ensure that each sampling procedure in obtaining the data will be correct and acceptable. In order to guarantee the quality of data, the researcher must always consider the uniqueness, accuracy and completeness of the values (Geiger, 2007).

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