STAT463-15S1 (C) Semester One 2015

Multivariate Statistical Methods

15 points

Details:
Start Date: Monday, 23 February 2015
End Date: Sunday, 28 June 2015
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 8 March 2015
  • Without academic penalty (including no fee refund): Sunday, 24 May 2015

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.

The application of these methods is blooming with the availability of large datasets from a wide range of scientific fields, combined with the advent of computing power to implement them. Examples abound in fields as diverse as bioinformatics, internet traffic analysis, clinical trials, finance and marketing. This course will cover the theory and applications of various multivariate statistical methods.

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

Daniel Gerhard

Assessment

Assessment Due Date Percentage 
Assignments 40%
Final Examination 60%


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 $887.00

* 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 .

All STAT463 Occurrences

  • STAT463-15S1 (C) Semester One 2015
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