ORIE 5740

ORIE 5740

Course information provided by the Courses of Study 2021-2022.

Examines the statistical aspects of data mining, the effective analysis of large datasets. Covers the process of building and interpreting various statistical models appropriate to such problems arising in scientific and business applications. Topics include naïve Bayes, graphical models, multiple regression, logistic regression, clustering methods and principal component analysis. Assignments are done using one or more statistical computing packages.

When Offered Spring.

Prerequisites/Corequisites Prerequisite: ORIE 3500, MATH 2940 or equivalent, programming experience. Exposure to multiple linear regression and logistic regression strongly recommended.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion. Combined with: ORIE 4740

  • 4 Credits Graded

  • 17889 ORIE 5740   LEC 001

    • TR Online Meeting
    • Jan 24 - May 10, 2022
    • Davis, D

  • Instruction Mode: Online
    Enrollment restricted to graduate students. Early Admit MEng students and OR&E Honors Program students may enroll with department approval.

  • 18407 ORIE 5740   DIS 201

  • Instruction Mode: In Person

  • 18408 ORIE 5740   DIS 202

  • Instruction Mode: In Person

  • 18409 ORIE 5740   DIS 203

  • Instruction Mode: In Person

  • 18410 ORIE 5740   DIS 204

  • Instruction Mode: In Person