Multivariate Data Analysis (2017)

Welcome to Multivariate Data Analysis

 

Description: In many applications data is acquired from multiple sources or is described by multiple variables. Within areas of signal and image processing, biomechanics, clinical decision support, bioinformatics, etc. there is an increasing need for analysing various types of multivariate data containing both dependent (outcome) and independent (predictor) variables. Instead of analysing the data by treating it as a task of multiple univariate problems the methods in this course fully encompasses the task as a single multivariate problem. In effect, the covariate nature of the data is analysed by examining relationships among multiple variables at the same time. The content of the course will cover both representation, transformation, and visualization of multivariate data as well as multivariate methods for statistical analysis, pattern recognition and test evaluation. The tentative course program is:

 

  • Probabilistic classification
    • Bayesian decision theory
    • Multivariate density
  • Non-parametric classification
    • Linear discriminant functions
    • Support Vector Machines
    • Clustering
  • Data analysis and test evaluation
    • Data representation, visualization, transformation (PCA/ICA)
    • ROC analysis
    • Cross validation
  • Multivariate statistics
    • Multivariate analysis of variance
    • Multivariate regression analysis

Literature:

Duda, Hart, Stork, Pattern Classification, 2nd Edition, Wiley

Jerrold H. Zar, Biostatistical Analysis, 5th Edition, Pearson (or alternative literature)

Prerequisites: Statistics, Matlab (basic skills), SPSS (basic skills).

Evaluation: Evaluation of the course will be based on active participation in the course including practical exercises in Matlab and SPSS.

Organizers and lecturers:Associate Professor Lasse Riis Østergaard, email: lasse@hst.aau.dk and Associate Professor Carsten Dahl Mørch, email: cdahl@hst.aau.dk

ECTS: 2

Time: 2., 9., 13., and 23. October 2017 (8:15-12:00)

Place: Aalborg University, Niels Jernes Vej 14, room 4.117

Zip code:

City: Aalborg

Number of seats: 25

Deadline: 11. September 2017

 

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.