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Fall 2016 Semester
Feb 22, 2018
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PPUA 6301 - Introduction to Computational Statistics
Introduces the fundamental techniques of quantitative data analysis, ranging from foundational skills—such as data description and visualization, probability, and statistics—to the workhorse of data analysis and regression, to more advanced topics—such as machine learning and networks. Emphasizes real-world data and applications using the R statistical computing language. Analyzing and understanding complex data has become an essential component of numerous fields: business and economics, health and medicine, marketing, public policy, computer science, engineering, and many more. Offers students an opportunity to finish the course ready to apply a wide variety of analytic methods to data problems, present their results to nonexperts, and progress to more advanced course work delving into the many topics introduced here.
4.000 Credit hours
4.000 Lecture hours

Levels: Graduate
Schedule Types: Seminar

Pub Policy and Urban Affairs Department

Course Attributes:
GS Col Socl Sci & Humanities

Restrictions:
Must be enrolled in one of the following Levels:     
      Graduate

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