Course Name Code Semester T+U Hours Credit ECTS
Econometrics I EKO 203 3 3 + 0 3 5
Precondition Courses
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Compulsory
Course Coordinator Prof.Dr. HİLAL YILDIZ
Course Lecturers Prof.Dr. HİLAL YILDIZ,
Course Assistants
Course Category Available Basic Education in the Field
Course Objective It is aimed to explain the economic theories via advanced quantitative techniques.
Course Content Quantitative methods are used to make estimation and forecasting in analyzes of the economic theory and studies. (1) Students learn basic statistical techniques for economic analyzes.(2) They gain ability to understand the studies of economists? more easily.(3) They gain experience of stating econometrically the research subjects.
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Hs/she knows that economic theory with quantitative approach Lecture, Testing,
2 he/she describe the concepts of the econometric methodology. Lecture, Testing, Oral Exam,
3 He/she makes a regression analysis by the method of least squares method. Lecture, Question-Answer, Testing, Oral Exam, Homework,
4 She/he knows regression analysis that single equation and examines regression hypotesis estimates. Lecture, Drilland Practice, Testing, Homework,
5 She/he performs estimates with synonym equation systems Lecture, Testing, Homework,
6 She/he uses all econometrics software in real problems (SPSS; EViews,...) Lecture, Question-Answer, Testing, Homework,
7 She/he defines stages of economteric modelling Lecture, Question-Answer, Testing, Oral Exam, Homework,
8 She/he make tests econometric assumptions Lecture, Drilland Practice, Testing, Homework,
9 She/he make tests related with hypotesis Lecture, Testing, Homework,
10 She/he uses quantitative tecnics to solve econometric problems Lecture, Question-Answer, Testing, Homework,
11 She/he detects the presence of heteroscedasticity, multicollinearity and autocorrelation problems, Lecture, Testing,
12 She/he reviews outcomes of the software programs Lecture, Testing, Oral Exam,
13 She/he makes test related with parameters which estimated with linear programs Lecture, Question-Answer, Testing, Oral Exam, Homework,
14 She/he makes significance test for models Lecture, Drilland Practice, Testing, Homework,
15 She/he make estimation of autoregressive models and interpretations Lecture, Drilland Practice, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Explanation of econometric concepts.
2 Expalanation of population regression function(prf) and sample regression function(srf)
3 Estimation of basic regression equation by Ordinary Least Squares method.
4 Introduction of SPSS packaged software.
5 Estimation of regression equation by SPSS packaged software
6 Testing of estimators acquired from regression equation by hypothesis tests
7 Application of estimators in SPSS programme.
8 Estimation of multivariate regression equation
9 Examining of the assumptions related to multivariate regression equation
10 Testing of multivariate regression equation in several significance levels.
11 Economic interpretation of estimators acquired from regression equation
12 Explanation of prediction problem and the kinds of prediction
13 Transformation of nonlinear equations into linear equations by using logarithmic methods.
14 Estimation of multivariate regression equation via matrix techniques.
Resources
Course Notes Gujarati, D. Basic Econometrics, McGraw-Hill Company, 2003
Course Resources Wooldridge, J. Introductory Econometrics, South-Western Cengage learning, 2009

Akkaya, Şahin ve Vedat Pazarlıoğlu. Ekonometri I, 2000

Tarı, Recep. Ekonometri, Umuttepe Yayınları, 2010
Week Documents Description size
0 Bölüm 1-min 2.9 MB
0 Bölüm 2-min 2.42 MB
0 Bölüm 1 2.9 MB
0 Bölüm 2 2.42 MB
0 Otokorelasyon 7.18 MB
0 Otokorelasyon 11.7 MB
0 ANOVA 3.54 MB
0 Matris 8.27 MB
Order Program Outcomes Level of Contribution
1 2 3 4 5
1 X
2 X
3 X
4 X
5 X
6 X
7 X
8 X
9 X
10 X
11 X
12 X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 70
1. Kısa Sınav 10
1. Ödev 10
2. Kısa Sınav 10
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Total Workload 0
Total Workload / 25 (Hours) 0
dersAKTSKredisi 5