STAT 5330

Data Mining

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Course Description

Pre-Requisite(s): Previous or concurrent enrollment in STAT 5120 or STAT 6120

This course introduces a plethora of methods in data mining through the statistical point of view. Topics include linear regression and classification, nonparametric smoothing, decision tree, support vector machine, cluster analysis and principal components analysis. Conceptual discussion in lectures is supplemented with hands-on practice in applied data-analysis tasks using SAS or R statistical software.


  • Xiwei Tang

     Rating

    3.00

     Difficulty

    5.00

     GPA

    3.90

     Sections

    Last Taught

    Spring 2020

  • Tao Huang

     Rating

     Difficulty

     GPA

    3.80

     Sections

    Last Taught

    Fall 2010

  • Xiaohui Wang

     Rating

     Difficulty

     GPA

    3.92

     Sections

    Last Taught

    Spring 2012

  • Caitlin Steiner

     Rating

     Difficulty

     GPA

    3.37

     Sections

    Last Taught

    Fall 2017

  • Faculty Staff

     Rating

     Difficulty

     GPA

     Sections

    Last Taught

    Fall 2020

  • Shan Yu

     Rating

     Difficulty

     GPA

    3.77

     Sections

    Last Taught

    Fall 2022

  • To Announced

     Rating

     Difficulty

     GPA

     Sections

    Last Taught

    Fall 2023

  • Zach Lubberts

     Rating

     Difficulty

     GPA

     Sections

    1

    Last Taught

    Fall 2025