STAT 5330
Data Mining
Course Description
Prerequisites
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. Prerequisites: Previous or concurrent enrollment in STAT 5120 or STAT 6120.
Instructors
Shounak Chattopadhyay
Fall 2026
mowe 3:30pm - 4:45pm
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Rating
—
Difficulty
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GPA
Zach Lubberts
Fall 2025
MoWe 3:30pm - 4:45pm
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Rating
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Difficulty
3.92
GPA
To Announced
Fall 2023
MoWe 3:30pm - 4:45pm
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Rating
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Difficulty
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GPA
Shan Yu
Fall 2022
MoWeFr 10:00am - 10:50am
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Rating
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Difficulty
3.77
GPA
Faculty Staff
Fall 2020
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Rating
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Difficulty
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GPA
Xiwei Tang
Spring 2020
1.0
Rating
5.0
Difficulty
3.90
GPA
Caitlin Steiner
Fall 2017
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Rating
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Difficulty
3.37
GPA
Xiaohui Wang
Spring 2012
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Rating
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Difficulty
3.92
GPA
Tao Huang
Fall 2010
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Rating
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Difficulty
3.80
GPA