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 sectorspecific models  3  To be able to construct linear, parabolic, semiparabolicdouble 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 corequisities 
None 
Recommended Optional Programme Components 
None 
Course Contents 
Topic of Econometrics  Some basic mathematical rules  Basic statistical rules  Micro, macro, and sectorspecific models  Econometric model patterns (Linear, parabolic, semiparabolicdouble 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 

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 sectorspecific models    4  Econometric model patterns (Linear, parabolic, semiparabolicdouble 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   

Recommended or Required Reading 
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  
Midterm Examination  1  100  SUM  100  
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 

Workload Calculation 