Information Package / Course Catalogue
Time Series Analysis
Course Code: BİS624
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 2
Prt.: 2
Credit: 3
Lab: 0
ECTS: 4
Objectives of the Course

To provide time series theory and methods such that it is possible to attend advanced time series courses and to perform real data analysis in a critical way.

Course Content

Understanding the properties of time series, to adopt the methods of analysis and forecasting for future reporting.

Name of Lecturer(s)
Learning Outcomes
1.Understanding the properties of time series data
2. Teaching forecasting models in time series analysis,
3.Relationship analysis of time series data
4.Interpret the outputs of time series models
5.Programs for the effective use of application.
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Conceptual Approach for Time Series: features, data transformations, time series components
Week 1 - Practice
Applications with package programs
Week 2 - Theoretical
Stochastic Processes and Differential Equations: Determining the number of delay
Week 2 - Practice
Applications with package programs
Week 3 - Theoretical
The concept of stationary in time series
Week 3 - Practice
Applications with package programs
Week 4 - Theoretical
Autocorrelation function and correlogram analysis
Week 4 - Practice
Applications with package programs
Week 5 - Theoretical
Exponential smoothing methods
Week 5 - Practice
Applications with package programs
Week 6 - Theoretical
Data filtering, filter types
Week 6 - Practice
Applications with package programs
Week 7 - Theoretical
Unit Root Tests for Time Series: hypotheses and interpreting
Week 7 - Practice
Applications with package programs
Week 8 - Theoretical
Literature review and discussion (Midterm exam)
Week 9 - Theoretical
Autoregressive Process- AR Process and moving average process-MA process, ARMA process
Week 9 - Practice
Applications with package programs
Week 10 - Theoretical
Box-Jenkins Methodology and ARIMA Model
Week 10 - Practice
Applications with package programs
Week 11 - Theoretical
Vector Autoregressive Model
Week 11 - Practice
Applications with package programs
Week 12 - Theoretical
Causality Tests
Week 12 - Practice
Applications with package programs
Week 13 - Theoretical
Analysis of cointegration
Week 13 - Practice
Applications with package programs
Week 14 - Theoretical
Analysis techniques
Week 14 - Practice
Applications with package programs
Week 15 - Final Exam
Final exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Attending Lectures1%5
Assignment1%5
Midterm Examination1%20
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory140228
Lecture - Practice140228
Assignment1505
Quiz2114
Midterm Examination110111
Final Examination120121
TOTAL WORKLOAD (hours)97
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
4
3
5
4
3
3
2
OÇ-2
4
3
4
3
3
3
2
OÇ-3
3
5
5
5
3
4
5
OÇ-4
OÇ-5
4
4
4
5
3
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026