STAT463-12S2 (C) Semester Two 2012

Multivariate Statistical Methods

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): Friday, 20 July 2012
  • Without academic penalty (including no fee refund): Friday, 5 October 2012

Description

Multivariate Statistical Methods

STAT315 and STAT463 are courses in multivariate statistical methods. Multivariate statistical methods extract information from datasets which consist of variables measured on a number of experimental units. Due to the large memory capacity available and with the advent of computing power, these methods are now widely applied in a variety of fields, including bioinformatics, epidemiology, finance and marketing. The course will cover the theory and application of various multivariate statistical methods, namely: multiple regression, principal component analysis, factor analysis, discriminant analysis, and clustering methods. It will also introduce the statistical analysis software SAS, which is a powerful tool when dealing with large multivariate datasets. R-syntax will also be briefly explained. Special attention will be given to practical applications and the interpretation of the results.

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

  • The courses will:
  • introduce multiple and multivariate regression
  • introduce principle component analysis (PCA) and factor analysis (FA)
  • introduce discriminant analysis (DA) and clustering methods.
  • introduce the use of statistical analysis software SAS
  • give you experience in writing scientific and technical reports

    You will be able to:
  • choose appropriate method for analysis of your dataset
  • use SAS procedures to perform the analysis
  • be able to interpret the analysis results in such a way that a non-user of statistics can understand
  • write a scientific and technical report.

Prerequisites

Subject to approval of the Head of School.

Course Coordinator

Marco Reale

Lecturer

Elena Moltchanova

Assessment

Assessment Due Date Percentage 
Internal Assessment - TBA 70%
Final Examination 30%


Assignments give you practice in analysing data and presenting results in a written report. You will be expected to use SAS for analysis. The assignments provide an opportunity for you to learn not only statistical modeling techniques, but to develop your scientific writing skills.

The STAT463 course includes a project report and a presentation on a method not covered in the course.

Textbooks / Resources

Recommended Reading:

Hastie T, Tibshirani R, Friedman J. The Elements of Statistical Learning: Data Mining, Inference and Prediction (2001 or 2009) Springer, Ch 1-7 Johnson, R.A. and Wichern, D.W. (2002). Applied Multivariate Statistical Analysis. Fifth Edition. Prentice Hall.
Everitt, B. and Dunn, G. (2001). Applied Multivariate Data Analysis. Second Edition. Hodder Arnold.

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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