|
| Udgave: |
Forår 2013 NAT |
| Point: |
7,5 |
| Blokstruktur: |
4. blok |
| Skemagruppe: |
C |
| Fagområde: |
dat |
| Varighed: |
8 uger |
| Uddannelsesdel: |
Bachelor niveau |
| Kontaktpersoner: |
Sami Brandt |
| Andre undervisere: |
Sune Darkner |
| Skema- oplysninger: |
 Vis skema for kurset
Samlet oversigt over tid og sted for alle kurser inden for Lektionsplan for Det Naturvidenskabelige Fakultet Forår 2013 NAT |
| Undervisnings- form: |
Lectures, excercises and mandatory assignments
Lectures, excercises and mandatory assignments
|
| Formål: |
To provide a basic and broad introduction to the representation, analysis, and processing of sampled data; to introduce students simple statistical analysis of experimental data, and data visualization. Examples will be taken from real-world problems, such as measurements of internet traffic, stock market data or consumer data, digital sound and pictures, etc. In addition, to provide an introduction to programming tools suitable for data analysis. |
| Indhold: |
Introduction to data processing, and filtering;
Sampled data, sampling, frequency representation;
Probability theory and statistics, Bayesian inference;
Parameter estimation, Least squares method, Linear regression, Mathematical modeling; Multivariate statistics, Principal Component Analysis;
Presentation of analysis results, including visualization by simple plotting;
Introduction to MATLAB |
| Målbeskrivelse: |
After completing the course, students should be able to:
- Choose an appropriate data representation, and transform between space/time and frequency domains, filter in both space/time- and frequency domains.
- Apply probability theory and statistics for single and vector valued problems.
- Understand and apply the least squares method for linear modeling and estimation.
- Know and apply some mathematical modelling methods for sampled data.
- Know some useful multivariate methods and their use, especially principal component analysis (PCA) and the use of dimensionality reduction.
- Visualize low- and high-dimensional data by simple plots and images.
- Implement simple data analysis and modeling methods.
- Perform the analysis of experimental data using the methods learned during the course.
|
| Tilmelding: |
November 15 to December 1, 2012, via KUnet, www.kunet.dk |
| Faglige forudsætninger: |
DIMS or MatIntro, LinAlg, OOPD, SS. |
| Eksamensform: |
Continuous evaluation with internal grading using the 7-point scale given for 4-6 written homework assignments.
Re-exam: 20-minute oral exam in course curriculum without preparation; internal grading using the 7-point scale.
|
| Eksamen: |
Løbende evaluering.
Reeksamen: Mundtlig prøve d. 21. august 2013. |
| Kursus hjemmeside: |
 |
| Undervisnings- sprog: |
Kun engelsk
|
| Sidst redigeret: |
31/10-2012 |