GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
TIME SERIES ANALYSIS/İST4002
Course Title: TIME SERIES ANALYSIS
Credits 4 ECTS 8
Course Semester 8 Type of The Course Compulsory
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
Students can analyze time-dependent data.
Students demonstrate the ability to determine the best model for time series.
Students can analyze time series with R programming language.
Students can interpret the results of analysis.

 -- MODE OF DELIVERY
  The mode of delivery of this course is face to face.
 --WEEKLY SCHEDULE
1. Week  Basic concepts and general framework of time series analysis & R programming
2. Week  Smoothing with harmonic mean & R programming
3. Week  Classical smoothing & R programming
4. Week  Exponential smoothing & R programming
5. Week  Exponential smoothing & R programming
6. Week  Stationary: Conceptual discussion & R programming
7. Week  Non-stationary time series
8. Week  Determination methods of stationarity, Midterm
9. Week  AR and MA processes
10. Week  ARMA processes
11. Week  ARIMA processes
12. Week  SARIMA processes
13. Week  Unit root tests
14. Week  Modeling criteria and diagnostic analysis
15. Week  Final exam
16. Week  ------------------------------------------------------------------
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
40
 Assignment
3
15
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
4
56
 Weekly Tutorial Hours
0
 Reading Tasks
14
6
84
 Searching in Internet and Library
14
2
28
 Material Design and Implementation
0
 Report Preparing
2
5
10
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
10
10
 Final Exam and Preperation for Final Exam
1
10
10
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
198
 TOTAL WORKLOAD / 25: 
7.92
 Course Credit (ECTS): 
8
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. The statistical textbooks which include latest information about statistics, equipment and other resources supported by scientific approach on undergraduate level have theoretical and practical knowledge.X
22. Statisticians by using knowledge and skills acquired at bachelor degree level model, analyze, and interpret datasets.X
33. Statisticians identify and analyze the problems with current developments in statistic and also develop solutions based upon researches and proofs.X
44. Statisticians apply theoretical and practical knowledge acquired in Statistics at bachelor degree level to the current problems.X
55. Statisticians have the ability to use computer software and computing technology at the certain level required by statistics field.X
66. Statisticians take responsibility at disciplinary and interdisciplinary studies as an individual or a team member.X
77. Statisticians must have knowledge and ability to follow development in the field of Statistics, and must develop life long-learning attitudes.X
88. By using a foreign language, statistician can keep track of every statistical information, and communicate with colleagues.X
99. Applying the statistical knowledge in the professional sense, statistician has social, scientific, and ethical values.X
1010. A statistician must have the ability to social sensitivity and socialization.X
1111. During the process of inference, a statistician uses time efficiently with the analytical thinking ability.X
 -- NAME OF LECTURER(S)
   (Prof. Mehmet Akif BAKIR , Prof. Reşat KASAP)
 -- WEB SITE(S) OF LECTURER(S)
   (https://abs.gazi.edu.tr/mabakir , https://makifbakir.wordpress.com/ , https://abs.gazi.edu.tr/rkasap)
 -- EMAIL(S) OF LECTURER(S)
   (mabakir@gazi.edu.tr , rkasap@gazi.edu.tr)