Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| TIME SERIES | - | Spring Semester | 3+0 | 3 | 8 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | Second Cycle (Master's Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Abdulbari BENER |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | To teach students to write a scientific article about time series analysis. The student learns how to analyze these series using the related methods by E-views when there are two or more time series. |
| Course Content | This course contains; Introduction to Time Series Analysis ,Time Series Analysis Assumptions,Stationary Processes in the Frequency Domain,Spectral Analysis,Time Series Simulation Analysis ,Time Series Simulation Analysis-2,Basic Descriptive Techniques,Linear Time Series Models,Fitting Time Series Models ,Forecasting,Bivariate Processes,State-Space Models and the Kalman Filter,Applicatons,Application-2. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Determines one of these topics and has detailed information about it | 12, 14, 6 | E |
| Describes the basics of topics in time series analysis | 10, 16, 6, 9 | A, E |
| Understands the academic writing in time series analysis for an article | 14, 6, 9 | E |
| Understands how to code a program on time series analysis | 12, 6, 9 | E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Time Series Analysis | Lecture Notes |
| 2 | Time Series Analysis Assumptions | Lecture Notes |
| 3 | Stationary Processes in the Frequency Domain | Lecture Notes |
| 4 | Spectral Analysis | Lecture Notes |
| 5 | Time Series Simulation Analysis | Lecture Notes |
| 6 | Time Series Simulation Analysis-2 | Lecture Notes |
| 7 | Basic Descriptive Techniques | Lecture Notes |
| 8 | Linear Time Series Models | Lecture Notes |
| 9 | Fitting Time Series Models | Lecture Notes |
| 10 | Forecasting | Lecture Notes |
| 11 | Bivariate Processes | Lecture Notes |
| 12 | State-Space Models and the Kalman Filter | Lecture Notes |
| 13 | Applicatons | Lecture Notes |
| 14 | Application-2 | Lecture Notes |
| Resources |
| 1.Schelter, B., Timmer, J., Winterhalder, M., 2006, Handbook of Time Series Analysis: Recent Theoretical Developments and Applications,Wiley. 2. Richard A. D., 2009, Time Series: Theory and Methods, Springer Verlag. 3. Tsay, R. S., 2010, Analysis of Financial Time Series, Wiley. |
| Agung, G.N., 2009, Time Series Data Analysis Using Eviews, Wiley. Enders, W., 1995, Applied Econometric Time Series, John Wiley & Sons Inc. Wei, W.W.S., 1990, Time Series Analysis, Addison-Wesley Publishing Company. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can use advanced theoretical and applied knowledge gained in the fields of theoretical and applied biostatistics. | X | |||||
| 2 | Can use the knowledge of basic probability and statistics theories and applications at the level of expertise. | X | |||||
| 3 | They have knowledge of all kinds of research design in the field of health | X | |||||
| 4 | Can design, construct and propose solutions for research in the field of health. | X | |||||
| 5 | Can identify and analyze problems in health research and produce solutions based on scientific methods | X | |||||
| 6 | Conducts scientific clinical descriptive or analytical research on priority issues related to the field. | X | |||||
| 7 | Evaluate and explain the information about the field of biostatistics with a critical approach. | X | |||||
| 8 | Observes and teaches social, scientific, and ethical values in the stages of data collection, recording, interpretation, and reporting related to the field of biostatistics. | X | |||||
| 9 | To be familiar with the software commonly used in the fields of biostatistics and to be able to use at least one effectively | X | |||||
| 10 | Conducts studies in the field of biostatistics independently or as a team. | X | |||||
| 11 | Maintains work in the field of biostatistics individually or as a team, can participate in the decision-making process, and make and finalize the necessary planning by using time effectively. | X | |||||
| 12 | Ensure the continuity of her professional development by using the biostatistics field and lifelong learning principles. | X | |||||
| 13 | Publishes a scientific article in a national and international journal or presents it at a scientific meeting. | X | |||||
| 14 | Take part in research, projects and activities in collaboration with other disciplines in the field of health. | X | |||||
| 15 | A sensitive individual, they can use their knowledge for the benefit of society and have sufficient awareness about quality management, occupational safety, and environment in all processes. | X | |||||
| 16 | Can use the knowledge and problem-solving skills synthesized in the field of biostatistics by considering ethical principles in health research. | X | |||||
| 17 | It can be found in national and international policy studies in the field of biostatistics and education. | X | |||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |
| ECTS / Workload Table | ||||||
| Activities | Number of | Duration(Hour) | Total Workload(Hour) | |||
| Course Hours | 0 | 0 | 0 | |||
| Guided Problem Solving | 0 | 0 | 0 | |||
| Resolution of Homework Problems and Submission as a Report | 0 | 0 | 0 | |||
| Term Project | 0 | 0 | 0 | |||
| Presentation of Project / Seminar | 0 | 0 | 0 | |||
| Quiz | 0 | 0 | 0 | |||
| Midterm Exam | 0 | 0 | 0 | |||
| General Exam | 0 | 0 | 0 | |||
| Performance Task, Maintenance Plan | 0 | 0 | 0 | |||
| Total Workload(Hour) | 0 | |||||
| Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(0/30) | 0 | |||||
| ECTS of the course: 30 hours of work is counted as 1 ECTS credit. | ||||||
Detail Informations of the Course
Course Description
| Course | Code | Semester | T+P (Hour) | Credit | ECTS |
|---|---|---|---|---|---|
| TIME SERIES | - | Spring Semester | 3+0 | 3 | 8 |
| Course Program |
| Prerequisites Courses | |
| Recommended Elective Courses |
| Language of Course | English |
| Course Level | Second Cycle (Master's Degree) |
| Course Type | Elective |
| Course Coordinator | Prof.Dr. Abdulbari BENER |
| Name of Lecturer(s) | Prof.Dr. Mehmet KOÇAK |
| Assistant(s) | |
| Aim | To teach students to write a scientific article about time series analysis. The student learns how to analyze these series using the related methods by E-views when there are two or more time series. |
| Course Content | This course contains; Introduction to Time Series Analysis ,Time Series Analysis Assumptions,Stationary Processes in the Frequency Domain,Spectral Analysis,Time Series Simulation Analysis ,Time Series Simulation Analysis-2,Basic Descriptive Techniques,Linear Time Series Models,Fitting Time Series Models ,Forecasting,Bivariate Processes,State-Space Models and the Kalman Filter,Applicatons,Application-2. |
| Dersin Öğrenme Kazanımları | Teaching Methods | Assessment Methods |
| Determines one of these topics and has detailed information about it | 12, 14, 6 | E |
| Describes the basics of topics in time series analysis | 10, 16, 6, 9 | A, E |
| Understands the academic writing in time series analysis for an article | 14, 6, 9 | E |
| Understands how to code a program on time series analysis | 12, 6, 9 | E |
| Teaching Methods: | 10: Discussion Method, 12: Problem Solving Method, 14: Self Study Method, 16: Question - Answer Technique, 6: Experiential Learning, 9: Lecture Method |
| Assessment Methods: | A: Traditional Written Exam, E: Homework |
Course Outline
| Order | Subjects | Preliminary Work |
|---|---|---|
| 1 | Introduction to Time Series Analysis | Lecture Notes |
| 2 | Time Series Analysis Assumptions | Lecture Notes |
| 3 | Stationary Processes in the Frequency Domain | Lecture Notes |
| 4 | Spectral Analysis | Lecture Notes |
| 5 | Time Series Simulation Analysis | Lecture Notes |
| 6 | Time Series Simulation Analysis-2 | Lecture Notes |
| 7 | Basic Descriptive Techniques | Lecture Notes |
| 8 | Linear Time Series Models | Lecture Notes |
| 9 | Fitting Time Series Models | Lecture Notes |
| 10 | Forecasting | Lecture Notes |
| 11 | Bivariate Processes | Lecture Notes |
| 12 | State-Space Models and the Kalman Filter | Lecture Notes |
| 13 | Applicatons | Lecture Notes |
| 14 | Application-2 | Lecture Notes |
| Resources |
| 1.Schelter, B., Timmer, J., Winterhalder, M., 2006, Handbook of Time Series Analysis: Recent Theoretical Developments and Applications,Wiley. 2. Richard A. D., 2009, Time Series: Theory and Methods, Springer Verlag. 3. Tsay, R. S., 2010, Analysis of Financial Time Series, Wiley. |
| Agung, G.N., 2009, Time Series Data Analysis Using Eviews, Wiley. Enders, W., 1995, Applied Econometric Time Series, John Wiley & Sons Inc. Wei, W.W.S., 1990, Time Series Analysis, Addison-Wesley Publishing Company. |
Course Contribution to Program Qualifications
| Course Contribution to Program Qualifications | |||||||
| No | Program Qualification | Contribution Level | |||||
| 1 | 2 | 3 | 4 | 5 | |||
| 1 | Can use advanced theoretical and applied knowledge gained in the fields of theoretical and applied biostatistics. | X | |||||
| 2 | Can use the knowledge of basic probability and statistics theories and applications at the level of expertise. | X | |||||
| 3 | They have knowledge of all kinds of research design in the field of health | X | |||||
| 4 | Can design, construct and propose solutions for research in the field of health. | X | |||||
| 5 | Can identify and analyze problems in health research and produce solutions based on scientific methods | X | |||||
| 6 | Conducts scientific clinical descriptive or analytical research on priority issues related to the field. | X | |||||
| 7 | Evaluate and explain the information about the field of biostatistics with a critical approach. | X | |||||
| 8 | Observes and teaches social, scientific, and ethical values in the stages of data collection, recording, interpretation, and reporting related to the field of biostatistics. | X | |||||
| 9 | To be familiar with the software commonly used in the fields of biostatistics and to be able to use at least one effectively | X | |||||
| 10 | Conducts studies in the field of biostatistics independently or as a team. | X | |||||
| 11 | Maintains work in the field of biostatistics individually or as a team, can participate in the decision-making process, and make and finalize the necessary planning by using time effectively. | X | |||||
| 12 | Ensure the continuity of her professional development by using the biostatistics field and lifelong learning principles. | X | |||||
| 13 | Publishes a scientific article in a national and international journal or presents it at a scientific meeting. | X | |||||
| 14 | Take part in research, projects and activities in collaboration with other disciplines in the field of health. | X | |||||
| 15 | A sensitive individual, they can use their knowledge for the benefit of society and have sufficient awareness about quality management, occupational safety, and environment in all processes. | X | |||||
| 16 | Can use the knowledge and problem-solving skills synthesized in the field of biostatistics by considering ethical principles in health research. | X | |||||
| 17 | It can be found in national and international policy studies in the field of biostatistics and education. | X | |||||
Assessment Methods
| Contribution Level | Absolute Evaluation | |
| Rate of Midterm Exam to Success | 50 | |
| Rate of Final Exam to Success | 50 | |
| Total | 100 | |