ORIE 4740

ORIE 4740

Course information provided by the 2015-2016 Catalog.

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.


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

When Offered Spring.

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

  • 4 Credits Graded

  • 11319 ORIE 4740   LEC 001

  • Instruction Mode: In Person

    Project work continues through end of term.

  • 11320 ORIE 4740   DIS 201

  • Instruction Mode: In Person

  • 11321 ORIE 4740   DIS 202

  • Instruction Mode: In Person

  • 11322 ORIE 4740   DIS 203

  • Instruction Mode: In Person

  • 17187 ORIE 4740   DIS 204

  • Instruction Mode: In Person

  • 18338 ORIE 4740   DIS 205

  • Instruction Mode: In Person