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Apr 24, 2017 by Subrata Kundu (kundu)
STAT 6240 : Statistical Data Mining
Mon, 24 Apr 2017 08:03:43 GMT
Sun, 16 Apr 2017 17:23:28 GMT
Catalog Pages referencing this course
Columbian College of Arts and Sciences
Long Course Title
Statistical Data Mining
Short Course Title
Statistical Data Mining
Number of Credits
Default Grading Method
statistics majors or with the permission of the instructor
Repeatable for Credit?
STAT 6201, STAT 6202, and STAT 6214 or equivalents
coursework in mathematical statistics, applied linear models, and multivariate statistics
Tatiyana V. Apanasovich,
Frequency of Offering
Are there Course Equivalents?
Are Fees Applicable?
Explanation and Description of Fees
Are Additional Resources Required?
Explanation of Additional Resources
Justification for Additional Resources
Describe any Sources of Additional Funding
Introduction to basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency. Students are expected to be familiar with R programming.
Objective: The student will be able to properly formulate data mining problems, understand and utilize fundamental data mining techniques, and evaluate the data mining results.
Learning Outcomes: By the end of the class, the student will be able to
1. Display a comprehensive understanding of different data mining tasks and the algorithms most appropriate for addressing them.
2. Demonstrate capacity to perform a self directed piece of practical work that requires the application of data mining techniques.
3. Conceptualize a data mining solution to a practical problem.
Uploaded a Course Syllabus
Explanation of how the course differs from similar GW courses
This course is about statistical methods in Data mining. It is less about specific tools and more about concepts and techniques and statistical methods in Data mining.
This was offered as a Topic Course (STAT 6289) in Fall 2016 and Spring 2017.
Course Reviewer Comments
Thu, 16 Feb 2017 21:29:21 GMT
Rollback: The Middle States Commission on Higher Education now requires that all syllabi include average minimum amount of out-of-class or independent learning expected per week. For more detail see https://provost.gwu.edu/files/downloads/Resources/Assignment-of-Credit-Hours_Final_Oct-2016.pdf