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| HRT4039 | Time Series Analysis | 2+0+0 | ECTS:4 | | Year / Semester | Fall Semester | | Level of Course | First Cycle | | Status | Elective | | Department | DEPARTMENT of GEOMATICS ENGINEERING | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 2 hours of lectures per week | | Lecturer | Prof. Dr. Emine TANIR KAYIKÇI | | Co-Lecturer | | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | To teach basic concepts and models of time series analysis and apply these models on geodetic time series analysis. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | can learn basic concepts of time series | 1,2 | | | LO - 2 : | can perfom trend analysis for time series and evaluate results | 1,2 | | | LO - 3 : | can perfom seasonel component analysis for time series and evaluate results | 1,2 | | | LO - 4 : | can perform outlier detection in time series | 1,2 | | | LO - 5 : | can write MATLAB programming code for time series analysis | 1,2,4 | | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
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Basic concepts of time series, time series components, trend and seasonal component analysis in time series |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Basic Concepts of Time Series | | | Week 2 | Preparing graphics for time series of different kind of data | | | Week 3 | Basic components of time series | | | Week 4 | Trend analysis of time series by parametric methods | | | Week 5 | Trend analysis of time series by parametric methods and application | | | Week 6 | Trend analysis of time series by non-parametric methods | | | Week 7 | Trend analysis of time series by non-parametric methods and Application | | | Week 8 | Mid Term Exam | | | Week 9 | Significancy tests of Trend components | | | Week 10 | Correlation Analysis of Time Series | | | Week 11 | Time Series Analysis in frequency Domain | | | Week 12 | Spectral Analysis of Time Series | | | Week 13 | Spectral Analysis of Time Series | | | Week 14 | Outlier Detection in Time Series | | | Week 15 | Outlier Detection in Time Series | | | Week 16 | Final Exam | | | |
| 1 | G. Kirchgässner, J.Wolters (2007). Introduction to Modern Time Series Analysis, ISBN 978-3-540-73290-7 Springer Berlin Heidelberg NewYork. | | | |
| 1 | C. Jekeli (2017). Spectral Methods in Geodesy and Geophysics, ISBN 13: 978-1-4987-4799-8. | | | 2 | Edited by B. Schelter, M. Winterhalder, and J. Timmer (2001). Handbook of Time Series Analysis:Recent Theoretical Developments and Applications, Wiley, ISBN-13: 978-3-527-40623-4. | | | 3 | Edited by H.-C. Ho, C.-K. Ing, T. L. Lai, (2000). Time Series and Related Topics, LECTURE NOTESMONOGRAPH SERIES, Volume 52, ISBN-13: : 978-0-940600-68-3. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 8 | | 1 | 30 | | Practice | 2
5
7
9
10
13 | | 0,5 | | | Homework/Assignment/Term-paper | 10 | | | 20 | | End-of-term exam | 15 | | 1 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 2 | 14 | 28 | | Sınıf dışı çalışma | 1 | 14 | 14 | | Arasınav için hazırlık | 12 | 1 | 12 | | Arasınav | 1 | 1 | 1 | | Ödev | 2 | 10 | 20 | | Dönem sonu sınavı için hazırlık | 18 | 1 | 18 | | Dönem sonu sınavı | 1 | 1 | 1 | | Diğer 1 | 1 | 6 | 6 | | Total work load | | | 100 |
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