Information Package / Course Catalogue
Econometric Software Packages
Course Code: EK353
Course Type: Area Elective
Couse Group: First Cycle (Bachelor's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 5
Objectives of the Course

This lecture aim at teaching econometric softwares which allow to do econometric and statistical estimations using computer.

Course Content

The lecture provides how to enter data and do econometric analysis using Excel, E-views, Stata and R programmes.

Name of Lecturer(s)
Assoc. Prof. Hatice AKDAĞ
Learning Outcomes
1.To be able to learn importing data in Excel, to do basic statistical calsulations and basic regression estimations in Excel
2.To be able to import data and do econometric analysis using E-views
3.To be able to test for autocorrelation, heteroskedasticity and multicollinearity in E-views and estimate dummy variable models
4.To be able to do panel data analysis using STATA
5.To be able to import data and advanced econometric analysis using R and STATA
Recommended or Required Reading
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Excel
Week 1 - Intermediate Exam
Midterm Exam
Week 2 - Practice
Calculations of standard error, mean, variance and basic regression analysis in Excel
Week 3 - Practice
Introduction to E-views: Importing data and basic data analysis using E-views
Week 4 - Practice
Basic Regression and Multiple Regression Estimations in E-Views
Week 5 - Practice
Autocorrelation, Heteroskedasticity and Multicollinearity tests using E-views
Week 6 - Practice
The estimation of Dummy Variable Models and Different Functional Models using E-views
Week 7 - Theoretical
Introduction to Stata: Importing data and basic regression analysis
Week 8 - Practice
Introduction to time-series, cross sectional datasets and panel datasets in Stata and applications on panel data analysis such as FE, RE and GMM
Week 9 - Practice
Introduction to time-series, cross sectional datasets and panel datasets in Stata and applications on panel data analysis such as FE, RE and GMM (Cont.)
Week 10 - Practice
Probit/Logit, Ordered Probit/Logit Estimations using Stata
Week 11 - Theoretical
Introduction to R: Importing data and general overview to the programme
Week 12 - Practice
Count Data Analysis using R
Week 13 - Practice
R ile sağ kalım analizi
Week 14 - Practice
Spatial Econometrics using R and STATA
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%40
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory32315
Lecture - Practice112355
Individual Work73235
Midterm Examination1819
Final Examination1819
TOTAL WORKLOAD (hours)123
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
3
3
3
3
3
3
3
3
3
OÇ-2
4
4
4
2
2
5
2
2
2
OÇ-3
3
3
3
3
4
4
2
2
2
OÇ-4
3
3
3
3
2
2
2
2
2
OÇ-5
2
2
2
5
2
2
2
2
2
Adnan Menderes University - Information Package / Course Catalogue
2026