IEM729 Regression Theory

6 ECTS - 3-0 Duration (T+A)- . Semester- 3 National Credit

Information

Code IEM729
Name Regression Theory
Term 2022-2023 Academic Year
Semester . Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. GÜLSEN KIRAL


Course Goal / Objective

The purpose of this course is to explain the advance regression methods for the research problems within the framework of general regression theory depending on the matrix and linear models.

Course Content

The course covers multiple linear regression, polynomial regression, principal component regression, logistic regression, probit and tobit regression.

Course Precondition

There are no prerequisites.

Resources

Doğrusal Regresyon Analizine Giriş (D.C. Montgomery, E.A. Peck and G.G. Vining (2001) Introduction to Linear Regression Analysis) Çeviri Editör : Prof.Dr. M Aydın Erar Nobel Yayın Evi.

Notes

Source books, statistical packages


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Specifies the relationships between variables.
LO02 Evaluates model building based on the relationships between variables.
LO03 Evaluates the model.
LO04 It predicts based on established models.
LO05 Defines the theoretical background of regression.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explains contemporary concepts about Econometrics, Statistics, and Operation Research
PLO02 Bilgi - Kuramsal, Olgusal Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research 3
PLO03 Bilgi - Kuramsal, Olgusal Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences 2
PLO04 Beceriler - Bilişsel, Uygulamalı Performs conceptual analysis to develop solutions to problems 4
PLO05 Beceriler - Bilişsel, Uygulamalı Models problems with Mathematics, Statistics, and Econometrics 3
PLO06 Beceriler - Bilişsel, Uygulamalı Interprets the results obtained from the most appropriate method to predict the model 2
PLO07 Beceriler - Bilişsel, Uygulamalı Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research 2
PLO08 Beceriler - Bilişsel, Uygulamalı Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution 4
PLO09 Beceriler - Bilişsel, Uygulamalı Searches for new approaches and methods to solve problems being faced 3
PLO10 Beceriler - Bilişsel, Uygulamalı Presents analysis results conveniently 4
PLO11 Beceriler - Bilişsel, Uygulamalı Collects/analyzes data in a purposeful way 4
PLO12 Yetkinlikler - İletişim ve Sosyal Yetkinlik Converts its findings into a master's thesis or a professional report in Turkish or a foreign language 3
PLO13 Beceriler - Bilişsel, Uygulamalı Develops solutions for organizations using Econometrics, Statistics, and Operation Research 1
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team 3
PLO16 Yetkinlikler - Öğrenme Yetkinliği Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study 3
PLO17 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code 2
PLO18 Yetkinlikler - İletişim ve Sosyal Yetkinlik Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form 2
PLO19 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on economic and social events by following current issues
PLO20 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values 2


Week Plan

Week Topic Preparation Methods
1 Introduction to regression analysis, regression analysis, definition and the purposes of regression analysis, data types, Regression and Correlation Analysis Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
2 Simple Linear Regression, the estimation of Regression coefficients with the OLS (Ordinary Least Squares Method) Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
3 the standard error of the regression model and coefficients, significance tests and confidence intervals, analysis of variance Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
4 The correlation coefficient, the coefficient of determination, and their significance tests Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
5 Random error term (residues-residues) assumptions about, examining the assumption of normality of the error term Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
6 To investigate the validity and reliability of the coefficients, elasticity coefficients, Multiple coefficient of determination Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
7 For the validity of the regression model analysis of varianceSimple and multiple regression models of non-linear autocorrelation Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Reading the relevant sections of the source book Ölçme Yöntemleri:
Yazılı Sınav
9 Assumptions about Random error term (residues-residues) , examining the assumption of normality of the error term Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
10 Autocorrelation problem identification and solutions. Multicollinearity problem Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
11 Constant variance assumption (Homoskedasite), variable variance (Heterodskedasite) state of constant variance revealed problems and solutions Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
12 problems and solutions of linear multicollinearity, example Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
13 Multiple linear regression models, alternative methods of selection of variables to be included in the model. Dummy variable models Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
14 Minitab and SPlus applications in solving regression models. Dummy dependent variable models Reading the relevant sections of the source book Öğretim Yöntemleri:
Anlatım
15 Homework presentation Reading the relevant sections of the source book Öğretim Yöntemleri:
Soru-Cevap
16 Term Exams Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Ölçme Yöntemleri:
Yazılı Sınav


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 3 42
Out of Class Study (Preliminary Work, Practice) 14 5 70
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 15 15
Final Exam 1 30 30
Total Workload (Hour) 157
Total Workload / 25 (h) 6,28
ECTS 6 ECTS

Update Time: 17.11.2022 09:14