STAT462-12S2 (C) Semester Two 2012

Data Mining

15 points

Details:
Start Date: Monday, 9 July 2012
End Date: Sunday, 11 November 2012
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 22 July 2012
  • Without academic penalty (including no fee refund): Sunday, 7 October 2012

Description

Data Mining

STAT318 and STAT462 are courses in Data Mining, suited to anyone with an interest in analysing data.  In these courses we introduce you to the statistical analysis of large datasets for both classification and association purposes.  
We cover analysis of both numeric and qualitative data and make use of the professional software package MATLAB.
In these courses we will show you how to use the package, enter, manipulate and analyze data in MATLAB.

The Courses will:
• introduce data mining.
• introduce advanced data analysis techniques including classification and regression trees, ROC curves and FP-growth algorithm.
• introduce the use of the statistics computer package MATLAB.

For a full list of 2012 Honours courses, please refer to the Department of Mathematics and Statistics Honours Booklet Mathematics and Statistics Honours Booklet

Learning Outcomes

  • describe and conduct appropriate statistical modeling techniques for large datasets
  • be able to interpret the model results in such a way that a non-user of statistics can understand
  • use MATLAB competently
  • write a scientific and technical report

Prerequisites

Subject to approval of the Head of School.

Course Coordinator / Lecturer

Carl Scarrott

Lecturer

Blair Robertson

Assessment

Assessment Due Date Percentage 
Internal Assessment - TBA 60%
Final Examination 40%


Assignments give you practice in analysing data and presenting results in a written report.
The project will give the opportunity to acquire presentation skills.

The lectures are complemented by computer labs where you will be guided in conducting approriate analysis and modelling.

Textbooks / Resources

Textbook
Recommended reading:
Tan, Steinbach and Kumar 2006. Introduction to Data Mining. 769pp.

This is on a restricted loan in the Library.

Indicative Fees

Domestic fee $788.00

* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.

For further information see Mathematics and Statistics .

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