Statistics for Predictive Analytics

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Course No: POMS.6120-061; SIS Class Nbr: 12536; SIS Term: 2830
Course Status: Open

Course Description

This course introduces statistical methods and techniques for predictive analytics. This is part of the business-analytics umbrella of courses. The main focus of this course is on regression, a powerful and widely used predictive method. Topics covered include simple linear regression, multiple regression, variable selection, model diagnostics, and systems of regression equations. The course also covers classification techniques using statistical methods such as linear discriminant function and logistic regression. Spreadsheet software, such as MS Excel, and statistical software, such as SAS and R, will be heavily utilized.

Prerequisites, Notes & Instructor

  • Prerequisites: POMS.6010 Operations Management, or Matriculated MS Business Analytics, or Business Analytics Certificate, or matriculated MS Engineering Management, or permission of program coordinator.
  • Special Notes:
  • Section Notes:
  • Credits: 3; Contact Hours: 3
  • Instructor: Nichalin Summerfield
  • Textbook Information

When Offered & Tuition

  • Online Course
  • Spring 2019: Jan 22 to Apr 07
  • Chat Hours: Mon 7:30-8:30pm*
  • Course Level: Graduate
  • Tuition: $1965
  • Note: There is a $30 per semester, nonrefundable registration fee for credit courses.

*Chat Hours provide an opportunity for the instructor and students to communicate in "real time". It is an informative and interactive session where course related questions, answers, and discussions take place. While student attendance during chat hours is not required, it is highly recommended. Weekly chat sessions are archived for students who are not able to participate in the live chat sessions at the scheduled times.

Related Programs: M.S. in Engineering Management

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