Students
Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
On campus
Duration
1 semesters
Details
Program Details
Degree
Bachelors
Major
Mathematics | Statistics
Area of study
Mathematics and Statistics
Education type
On campus
Course Language
English
About Program

Program Overview


Introduction to the University Program

The provided context does not contain information about a university program. Instead, it appears to be a cookie policy and website information for Aalborg University (AAU). However, a section about a module named "Tidsr熥keanalyse" (Time Series Analysis) is present, which seems to be related to an academic program.


Time Series Analysis Module

Module Description

The Time Series Analysis module builds upon the knowledge obtained in the Statistical Inference for Linear Models module. It covers topics such as conditioning in the multivariate normal distribution, ordinary and generalized least squares methods, and the resulting OLS and GLS estimators. The module also introduces time series analysis as a stochastic process, understanding the relationship between stochastic processes and dynamic systems, and explores Box-Jenkins models, particularly ARMA models.


Learning Objectives

Knowledge

  • Understand conditioning in the multivariate normal distribution and the concepts of OLS and GLS estimators.
  • Recognize time series analysis as a stochastic process and its connection to dynamic systems.
  • Familiarize with Box-Jenkins models, specifically ARMA models, and concepts of stationarity.
  • Understand various modern time series and time series econometric models within financial econometrics and financial engineering.

Skills

  • Theoretically interpret the statistical and econometric properties of time series models.
  • Perform all phases of a classical time series analysis: identification, estimation, model control, prediction, and statistical/econometric interpretation.
  • Use correlograms and other graphical tools in the identification phase.
  • Apply newer statistical methods for time series analysis.

Competences

  • Apply time series analysis concepts in an econometric or other practical context.
  • Conduct qualified econometric analyses on financial data and other time series data, including estimation and prediction using appropriate software.

Module Details

Module Code and Type

  • Module Code: 22BMAT6TIANL
  • Module Type: Course

Duration and ECTS

  • Duration: 1 semester
  • ECTS: 5

Language and Location

  • Teaching Language: Danish
  • Teaching Location: Campus Aalborg

Responsible Institute and Faculty

  • Responsible Institute: Institute for Mathematical Sciences
  • Faculty: The Faculty of Engineering and Science

Examination

Exam Form

  • Exam Name: Time Series Analysis
  • Exam Form: Written or oral
  • ECTS: 5
  • Assessment Form: 7-point scale
  • Examination Language: Danish

Evaluation Criteria

Evaluation criteria are stated in the University's Examination Regulations.


Module Responsibility

  • Module Responsible: Ege Rubak
  • Included in Study Programs for Bachelor and Master's degrees in Mathematics, Mathematics-Technology, and Mathematics-Economics.

Given the constraints and the nature of the input, the extracted information primarily focuses on the "Time Series Analysis" module rather than a broad university program. The details provided adhere to the specified markdown format and are presented in a formal, polished tone suitable for publication.


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