course-details-portlet

TK8117 - Multivariate Data Analysis - Advanced Topics

About

Examination arrangement

Examination arrangement: Oral examination and Work
Grade: Passed/Failed

Evaluation form Weighting Duration Examination aids Grade deviation
work 30/100
Oral examination 70/100

Course content

1. Brief repetition of a) Design of Experiments b) Analysis of one table (PCA et. al.) c) Analysis of two tables using mutlivariate regression Methods.
2. Modelling timedependent data e.g. batch data ond other processes With transient signals.
3. Analysis of multiblock data, e.g. sensor-fusion to obtain unique and common information i several data tables.
4. Multidomain modelling of processes which changes both in time and intensity (IDLE modell).
5. Strategies for analyzing 3-dimensional data by multiway methods, e.g. PARAFAC.
6.How to use models in real-time prediction and detection of outliers (multivariate process modelling)
7. Validation and feature extraction in multivariate models.

Learning outcome

KNOWLEDGE: The students shall get an overview of different methods for analysing data from processes that are continuous and/or time dependent. They shall be able to plan practical experiments using statistical principles. This includes sensor-fusion and hierarchical modelling of multiblock data.

SKILLS: The students shall be able to organize data form different types of measuring instruments, with different dimensions and consider optimal pretreatment of data. They shall be able to propose the most suitable methods given a specific application.


GENERAL COMPETENCE: Be able to use knowledge and skills on new applications. Be able to discuss topics related to the course with specialists in the topics and propose which methods from the course to use in interdisciplinary projects.

Learning methods and activities

Lectures incorporating practical examples. Project work on chosen datasets.

Course materials

Specified at the start of the course.

More on the course

No

Facts

Version: 1
Credits:  7.5 SP
Study level: Doctoral degree level

Coursework

Term no.: 1
Teaching semester:  AUTUMN 2020

No.of lecture hours: 2
Lab hours: 2
No.of specialization hours: 4

Language of instruction: English, Norwegian

Location: Trondheim

Subject area(s)
  • Chemometrics
  • Signal Processing
  • Multivariate Image Analysis
  • Design of Experiments
  • Engineering Cybernetics
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Engineering Cybernetics

Phone:

Examination

Examination arrangement: Oral examination and Work

Term Status code Evaluation form Weighting Examination aids Date Time Digital exam Room *
Autumn ORD work 30/100
Room Building Number of candidates
Spring ORD work 30/100
Room Building Number of candidates
Autumn ORD Oral examination 70/100
Room Building Number of candidates
Spring ORD Oral examination 70/100
Room Building Number of candidates
  • * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
Examination

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