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 FACULTY of SCIENCE / DEPARTMENT of STATISTICS and COMPUTER SCIENCES Course Catalog http://www.ktu.edu.tr/isbb Phone: +90 0462 +90 (462) 3773112 FENF
FACULTY of SCIENCE / DEPARTMENT of STATISTICS and COMPUTER SCIENCES /

 IST4012 Time Series Analysis 4+0+0 ECTS:6 Year / Semester Spring Semester Level of Course First Cycle Status Elective Department DEPARTMENT of STATISTICS and COMPUTER SCIENCES Prerequisites and co-requisites None Mode of Delivery Contact Hours 14 weeks - 4 hours of lectures per week Lecturer Dr. Öğr. Üyesi Erdinç KARAKULLUKÇU Co-Lecturer Language of instruction Turkish Professional practise ( internship ) None The aim of the course: 1. To introduce students to time series methods in detail. 2. To give information to the students at a level that can analyze time series data with the help of SPSS program.
 Learning Outcomes CTPO TOA Upon successful completion of the course, the students will be able to : LO - 1 : apply the basic methods used in univariate time series analysis. 1,2,3 1, LO - 2 : compare time series analysis methods and obtained results with each other. 1,2,3 1, LO - 3 : apply time series analysis using SPSS program. 1,2,3 1, LO - 4 : make predictions for the future using any univariate time series data. 1,2,3 1, 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
 Contents of the Course
 1. Basic concepts 2. Decomposition Method 3. Regression Analysis 4. Exponential Smoothing Method 5. Box-Jenkins Models
 Course Syllabus Week Subject Related Notes / Files Week 1 Basic concepts and fundemantal procedures Week 2 Introducing the parts of the SPSS program related to time series analysis Week 3 Decomposition method Week 4 Application of decomposition method using SPSS program Week 5 Regression models for series having trend Week 6 Application of regression models using SPSS program Week 7 Additive and multiplicative regression models Week 8 Application of additive and multiplicative regression models using SPSS program Week 9 Midterm exam week Week 10 Exponential Smoothing Methods for series having trend Week 11 Application of exponential smoothing methods using SPSS program Week 12 Additive and multiplicative exponential smoothing methods Week 13 Application of additive and multiplicative exponential smoothing methods using SPSS program Week 14 Box-Jenkins models Week 15 Application of Box-Jenkins models Week 16 Final exam week
 Textbook / Material
 1 Kadılar, C. ve Öncel Çekim, H. 2020; SPSS ve R Uygulamalı Zaman Serileri Analizine Giriş, Seçkin Yayınları, Ankara. 2 Kadılar, C. ve Öncel Çekim, H. 2020; SPSS ve R Uygulamalı Zaman Serileri Analizine Giriş, Seçkin Yayınları, Ankara.