Information Package / Course Catalogue
Cross Section Data Analysis
Course Code: ZTE606
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: 8
Objectives of the Course

To give practical experience in modelling for cross sectional agricultural data

Course Content

Econometric analysis of cross sectional data from farn management research esby means of least squares through Different mathematical forms, Specificaton tests, Heteroskedasticity tests, Multicollinearity tests, Weigted least squares applications, Dummy variables, Extensively used econometric software are used for practicing with sample data sets.

Name of Lecturer(s)
Prof. Osman Orkan ÖZER
Learning Outcomes
1.Ability of setting up linear econometric model
2.Making statistical tests for econometric models
3.Ability of estimating different mathematical models
4.Ability of applying necesarry tests for estimated models and improving the best models
5.Ability of using estimation results of models on decision making in economics and management.
Recommended or Required Reading
1.Greene, H.,W, Econometric Analysis (7th Edition), 2012, Stern School of Business, New York University
Weekly Detailed Course Contents
Week 1 - Theoretical
Econometric analysis of cross sectional data from farm management research esby means of least squares through Different mathematical forms
Week 2 - Theoretical
Econometric analysis of cross sectional data from farm management researches by means of least squares through Different mathematical forms
Week 3 - Theoretical
Economic Forecasting Model with Least Squares Method
Week 4 - Theoretical
Specificaton tests (F and t test)
Week 4 - Practice
Applications with econometrics software
Week 5 - Theoretical
Model identification tests: Wald test
Week 5 - Practice
Specificaton tests (Practice with softwares)
Week 6 - Theoretical
Model identification tests: Ramsey Reset
Week 6 - Practice
Specificaton tests (Practice with softwares)
Week 7 - Theoretical
Selection of Independent Variables I
Week 7 - Practice
Practice with softwares
Week 8 - Theoretical
Selection of Independent Variables I
Week 9 - Practice
Practice with softwares
Week 10 - Practice
Practice with softwares
Week 11 - Theoretical
Predicting in Common Mathematical Forms: Polynomial Functions
Week 12 - Theoretical
Dummy variables
Week 13 - Theoretical
Heteroskedasticity
Week 14 - Theoretical
Heteroskedasticity testleri
Week 14 - Practice
Heteroskedasticity testleri
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory1462112
Lecture - Practice142256
Midterm Examination115116
Final Examination115116
TOTAL WORKLOAD (hours)200
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
PÇ-8
PÇ-9
PÇ-10
OÇ-1
5
4
1
1
4
1
OÇ-2
1
4
1
2
OÇ-3
2
2
1
2
3
4
5
1
OÇ-4
5
4
1
2
1
2
3
1
OÇ-5
1
5
4
1
2
Adnan Menderes University - Information Package / Course Catalogue
2026