Temple University 3 credits STAT
Significant advances in technology have resulted in most organizations collecting enormous amounts of data both deliberately and incidentally in the course of doing business. Managing data on this scale and converting it into knowledge to facilitate decision making presents exciting new challenges. Although data is ubiquitous, real data is also often "dirty", corrupted with various forms of errors, or missing. Regardless of whether data is "clean", it may not be in the proper format for analysis, or data from multiple places may need to be merged in order for analysis to take place. Thus, the first step in generating good information from data is almost always to clean, process, and validate the data. The goal of this course is to explore tools and techniques for managing data, cleaning data (fixing errors, identifying outliers, etc.), extracting subsets or samples of data, merging and combining datasets, summarizing data, and dealing with the most common problems that may arise with data.
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