          Description of Individual Course Units
 Course Unit Code Course Unit Title Type of Course Unit Year of Study Semester Number of ECTS Credits İST002 ECONOMETRICS Elective 2 4 3
Level of Course Unit
First Cycle
Objectives of the Course
To give students the ability applying mathematics and statistics to economic data
Name of Lecturer(s)
Yrd.Doç.Dr. Özge ELMASTAŞ GÜLTEKİN
Learning Outcomes
 1 To have a knowledge about some basic mathematical and statistical rules 2 To learn micro, macro, and sector-specific models 3 To be able to construct linear, parabolic, semi-parabolic-double logarithmic econometric models 4 To be able to construct econometric models consisting of single explanatory variable 5 To be able to construct multiple regression model, to make inference and hypothesis test, to learn solution techniques with matrices 6 To have a knowledge about multicollinearity, varying variance and autocorrelation, to be able to determine spesification errors 7 To be able to construct models including dummy variables
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Topic of Econometrics - Some basic mathematical rules - Basic statistical rules - Micro, macro, and sector-specific models - Econometric model patterns (Linear, parabolic, semi-parabolic-double logarithmic)- Econometric models consisting of single variable- Multiple regression estimation and hypothesis tests, solution techniques with matrices- Deviations from classical regression model- Multicollinearity, varying variance, autocorrelation, specification errors, models including dummy variables.
Weekly Detailed Course Contents
 Week Theoretical Practice Laboratory 1 Topic of Econometrics - Some basic mathematical rules - Basic statistical rules 2 Topic of Econometrics - Some basic mathematical rules - Basic statistical rules 3 Micro, macro, and sector-specific models 4 Econometric model patterns (Linear, parabolic, semi-parabolic-double logarithmic) 5 Econometric models consisting of single variable (Single explanatory variable) 6 Multiple regression estimation and hypothesis tests 7 Solution techniques of multiple regression model with matrices 8 Deviations from classical regression model 9 Midterm exam 10 Multicollinearity, varying variance 11 Autocorrelation, specification errors 12 Models including dummy variables (One quantitative and one qualitative variables) 13 Models including dummy variables (One quantitative and one qualitative variables) 14 Models including dummy variables (One quantitative and two qualitative variables) 15 Models including dummy variables (One quantitative and two qualitative variables) 16 Final exam
Ertek, T., Ekonometriye giriş Akkaya, Ş., Pazarlıoğlu, V., Ekonometri I Gujarati, D.N., Basic Econometrics
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight Midterm Examination 1 100 SUM 100 End Of Term (or Year) Learning Activities Quantity Weight Final Sınavı 1 100 SUM 100 Term (or Year) Learning Activities 40 End Of Term (or Year) Learning Activities 60 SUM 100
Language of Instruction
Turkish
Work Placement(s)
None 