Information Package / Course Catalogue
Basic Econometrics
Course Code: MHY610
Course Type: Area Elective
Couse Group: Third Cycle (Doctorate Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

To gain the ability to use tools such as correlation and regression.

Course Content

Correlation analysis, simple and multiple regression analysis, individual and group significance test, determination coefficient , specification and functional structure and dummy variables.

Name of Lecturer(s)
Learning Outcomes
1.To be able to understand the difference between time series and cross-sectional data
2.To be able to define the purposes of econometrics model
3.To be able to choose model as reasonable econometrics method
4.To be able to analysis assumptions of econometrics model
5.To be able to make inferences from econometrics models s evidences
Recommended or Required Reading
1.EKONOMETRİ I ( 2000), Şahin AKKAYA-M.Vedat PAZARLIOĞLU, Anadolu Matbaacılık
Weekly Detailed Course Contents
Week 1 - Theoretical
The purpose of econometrics, the topic of econometrics and the preceding steps in econometrics research
Week 2 - Theoretical
Simple Linear Regression Model(Bivariate Regression Model), Least Square Regression Model and its assumptions.
Week 3 - Theoretical
Multiple Regression Model
Week 4 - Theoretical
Hypothesis Tests, Regression and Analysis of Variance
Week 5 - Theoretical
Hypothesis Tests, Regression and Analysis of Variance
Week 6 - Theoretical
Topics with Bivariate Regression Models
Week 7 - Theoretical
The Other Tests for econometrics models with one equation, selection of models criteria
Week 8 - Intermediate Exam
Midterm Exam
Week 9 - Theoretical
Distribtions for Normality and Normality tests, Multicollineartity, meaning of Multicollineartity, Estimations of Least Square Regression in case Multicollineartity, consequences after Multicollineartity, detected and remove Multicollineartity
Week 10 - Theoretical
Heteroscedasticity, meaning of Heteroscedasticity, Estimations of Least Square Regression in case Heteroscedasticity, consequences after Heteroscedasticity
Week 11 - Theoretical
Detected and remove Heteroscedasticity
Week 12 - Theoretical
Autocorrelation, meaning of Autocorrelation, Estimations of Least Square Regression in case Autocorrelation, consequences after Autocorrelation
Week 13 - Theoretical
Detection and removal of Autocorrelation
Week 14 - Theoretical
Applications
Week 15 - Theoretical
Applications
Week 16 - Final Exam
Final Exam
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%60
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory142370
Individual Work72228
Midterm Examination110111
Final Examination115116
TOTAL WORKLOAD (hours)125
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
OÇ-1
4
3
5
4
3
3
4
3
3
OÇ-2
5
4
3
3
4
5
4
3
4
OÇ-3
3
4
5
4
3
3
4
3
4
OÇ-4
4
5
4
3
4
3
5
4
3
OÇ-5
3
4
3
5
4
3
3
4
5
Adnan Menderes University - Information Package / Course Catalogue
2026