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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Simulation and Modeling * ISB   411 7 3 3 5

 Prerequisites and co-requisites Yok Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Prof.Dr. Mahmude Revan ÖZKALE
Instructors
 Prof.Dr. MAHMUDE REVAN ÖZKALE 1. Öğretim Grup:A Prof.Dr. MAHMUDE REVAN ÖZKALE 2. Öğretim Grup:A

Assistants
Goals
Time series modeling, forecasting and prediction, and the use of a variety of package programs related to them
Content
The components of the time series, the time series graphics, the decomposition methods, the regression models in time series, exponential smoothing techniques, Box-Jenkins Models, the statistical package programs

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
X
2
Emphasize the importance of Statistics in life
X
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
X
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
X
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
X
12
Construct a model and analyze it by using statistical packages
X
13
Distinguish the difference between the statistical methods
X
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Interpretation of time series and time-series graphics Source reading
2 Autocorrelation and partial autocorrelation functions Source reading
3 Examination of stationary Source reading
4 Portmanteau tests, the index numbers Source reading
6 Introduction to time series regression analysis, normality tests, the problem of heteroscedasticity Source reading
7 autocorrelation test, regression analysis in non-seasonal time series Source reading
8 Regression analysis in non-seasonal time series Source reading
9 Midterm exam Review the topics discussed in the lecture notes and sources
10 Regression analysis in seasonal tiem series Source reading
11 Exponential smoothing methods Source reading
12 Autoregression (AR) models and properties Source reading
13 Moving average (MA) models and properties Source reading
14 ARIMA models, parameter estimation Source reading
15 Dickey-Fuller unit root test Source reading
16-17 Final exam Review the topics discussed in the lecture notes and sources