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The course covers various types of data, as well as methods of its acquisition, processing, analysis, statistical interpretation and presentation in a format suitable for management meetings. Topics include using SPSS for the creation of charts, frequency distribution and histograms, summary statistics, linear regression and various statistical tests. The differences between typical spreadsheet forms of data management and databases are highlighted to help students determine appropriate courses of action for research design. The tasks of managing and analyzing data have become more intricate due to the rise of big data and its challenges: volume, velocity, and variety. Using robust software, such as DataMiner, or R, the student will learn how to process and analyze myriad structured, semi-structured and unstructured data, translating these into actionable insights and meaningful visual presentations.