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    | EKO2009 | Econometrics-I | 3+0+0 | ECTS:7 |  | Year / Semester | Fall Semester |  | Level of Course | First Cycle |  | Status	 | Compulsory |  | Department | DEPARTMENT of ECONOMETRICS |  | Prerequisites and co-requisites | None |  | Mode of Delivery |  |  | Contact Hours | 14 weeks - 3 hours of lectures per week |  | Lecturer | Prof. Dr. Rahmi YAMAK |  | Co-Lecturer | Prof. Dr. Rahmi YAMAK, |  | Language of instruction | Turkish |  | Professional practise ( internship )	 | None |  |   |   | The aim of the course: |  | The aim of this course is to teach basic econometrics methods used for testing the economics hypothesis. |  
 |  Learning Outcomes | CTPO | TOA |  | Upon successful completion of the course, the students will be able to : |   |    |  | LO - 1 :  | apply statistical methods for solving economics problems | 1 - 3 | 1, |  | LO - 2 :  | determine and empirically solve the economics problems | 1 - 3 | 1, |  | LO - 3 :  | model, estimate and interpret the economics problems | 1 - 3 | 1, |  | LO - 4 :  | analyze by using statistics, mathematics and economics | 1 - 3 | 1, |  | LO - 5 :  | have findings for future | 1 - 3 | 1, |  | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam,  3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation,  6: Term paper), LO : Learning Outcome   |  |   |    
			 | Simple regression models, multiple regression models, application of OLS to regression models, assumptions of OLS, t-tests, F-tests, detection and correction of multicollinearity, detection and correction of specification errors, dummy variables, interaction variables. |  
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 | Course Syllabus |  |  Week | Subject | Related Notes / Files |  |  Week 1 | Correlation Analysis |  |  |  Week 2 | Simple Regression Analysis |  |  |  Week 3 | Estimation and Interpretation of Simple Regression Equations |  |  |  Week 4 | Multiple Regression Analaysis |  |  |  Week 5 | Estimation and Interpretation of  Multiple Regression Equations |  |  |  Week 6 | Test of Significance for Individual Coefficients of Regression |  |  |  Week 7 | Anova Table and F-test |  |  |  Week 8 | Coefficient of Determination |  |  |  Week 9 | Mid-term exam  |  |  |  Week 10 | Specification in the Regression Equations |  |  |  Week 11 | Selection of Functional Structure in the Regression Equations |  |  |  Week 12 | Dummy Variables |  |  |  Week 13 | Interaction Variables |  |  |  Week 14 | Trend and Piecewise Regressions |  |  |  Week 15 | Multicollinearity |  |  |  Week 16 | End-of-term exam |  |  |   |   
 | 1 | Köseoğlu, M. , Yamak, R. , 2015; Uygulamalı İstatistik ve Ekonometri, Aksakal Kitabevi, Trabzon |  |  |   |   
 | 1 | Gujarati, D. , 1999; Temel Ekonometri (Çev. : Şenesen, Ü. , Şenesen, Gülay G. ) , İstanbul |  |  |   |   
 |  Method of Assessment  |  | Type of assessment | Week No | Date | Duration (hours) | Weight (%) |  |  Mid-term exam |  9 |  12.11.2023 |  1 |  50 |  |  End-of-term exam |  16 |  28.01.2024 |  1 |  50 |  |   |   
 |  Student Work Load and its Distribution  |  | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term |  |  Yüz yüze eğitim |  3 |  14 |  42 |  |  Sınıf dışı çalışma |  8 |  14 |  112 |  |  Arasınav için hazırlık |  10 |  2 |  20 |  |  Arasınav  |  1 |  1 |  1 |  |  Dönem sonu sınavı için hazırlık |  11 |  3 |  33 |  |  Dönem sonu sınavı |  2 |  1 |  2 |  | Total work load |  |  | 210 |  
  
                 
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