ORIE 4740

ORIE 4740

Course information provided by the Courses of Study 2019-2020.

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.

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Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one lecture and one discussion.

  • 4 Credits Stdnt Opt

  • 17567ORIE 4740  LEC 001

    • TROlin Hall 255
    • Jan 21 - May 5, 2020
    • Davis, D

  • Instruction Mode: Hybrid - Online & In Person

  • 17569ORIE 4740  DIS 201

  • Instruction Mode: Hybrid - Online & In Person

  • 17570ORIE 4740  DIS 202

  • Instruction Mode: Hybrid - Online & In Person

  • 17571ORIE 4740  DIS 203

  • Instruction Mode: Hybrid - Online & In Person

  • 17572ORIE 4740  DIS 204

  • Instruction Mode: Hybrid - Online & In Person