Analyzing numerical data validating identification numbers

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Data mining (the analysis step of the "Knowledge Discovery in Databases" process, or KDD), a relatively young and interdisciplinary field of computer science, is the process that results in the discovery of new patterns in large data sets.Researchers who utilize open-ended questions must be skilled interviewers since they need to record all information to avoid loss of important information, and the analysis is time-consuming.(2) In addition, open-ended questions can be difficult to analyze statistically because the data is not uniform and must be coded in some manner.(3)Examples of open-ended questions: Partially categorized questions are similar to open-ended questions, but some answers have already been pre-categorized to facilitate recording and analysis.There is also usually an alternative titled “other” with a black space next to it.The advantages of these types of questions are that answers can be recorded quickly, and the analysis is often easier.One of the major risks is that the respondent will pre-categorize too quickly, resulting in a potential loss of interesting and valuable information.Closely related to the Lorenz curve, the ABC curve visualizes the data by graphically representing the cumulative distribution function.

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