ECMZ202 Regression Analysis

6 ECTS - 3-0 Duration (T+A)- 4. Semester- 3 National Credit

Information

Code ECMZ202
Name Regression Analysis
Term 2024-2025 Academic Year
Semester 4. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 3 National Credit
Teaching Language İngilizce
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Dr. Öğr. Üyesi FELA ÖZBEY
Course Instructor
1 2
Dr. Öğr. Üyesi FELA ÖZBEY (A Group) (Ins. in Charge)


Course Goal / Objective

The aim of this course is to give the students a good theoretical and empirical understanding of statistical methods used in regression analysis.

Course Content

Concepts of statistics, data, population, sample, parameter, estimation, estimator; Qualitative and quantitative data; The normal probability distirbution; Sampling distirbutions and central limit theorem; Simple linear regression; Multiple linear regression; Fitting the model: the method of least squares; Assumptions of the model; Estimation of the variances (the error variance and parameter estimates variances); The coefficient of correlation; The coefficient of determination; Testing the validity of a model; The analysis of variance; Model building; Variable screening methods.

Course Precondition

None

Resources

William Mendenhan, Terry Sincich (2003), A Second Course in Statistics: Regression Analysis, Pearson Ecucation Inc., ISBN: 0-13-122810-2

Notes

Douglas C. Montgomery, Elizabeth A. Peck, G. Geoffrey Vining(2012) Introduction to Linear Regression Analysis, Fifth Edition, ISBN: 978-0470542811


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Distinguishes between qualitative and quantitative data.
LO02 Applies the Ordinary Least Squares method to estimate linear regression model.
LO03 Chooses the most appropriate model for the data.
LO04 Tests the validity of a model estimate.
LO05 Performs the variance anasysis.
LO06 Tests the statistical significance of the estimated parameters.
LO07 Lists the assumptions of the classical linear regression model.
LO08 Estimates a simple linear regression model using ordinary least squares.
LO09 Estimates a multiple linear regression model using ordinary least squares.
LO10 Calculates the determination coefficient.
LO11 Calculates the residual sum of squares.
LO12 Calculates the total sum of squares.
LO13 Calculates the sum of squares of regression.
LO14 Estimates the confidence intervals for model parameters.
LO15 Evaluates the confidence interval for the prediction.
LO16 Evaluates the confidence interval for the estimation.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Explain the basic concepts and theorems in the fields of Econometrics, Statistics and Operations research 5
PLO02 Bilgi - Kuramsal, Olgusal Acquires basic Mathematics, Statistics and Operation Research concepts 5
PLO03 Bilgi - Kuramsal, Olgusal Describes the necessary concepts of Business
PLO04 Beceriler - Bilişsel, Uygulamalı Equipped with the foundations of Economics, and develops Economic models 3
PLO05 Beceriler - Bilişsel, Uygulamalı Models problems with Mathematics, Statistics, and Econometrics 5
PLO06 Beceriler - Bilişsel, Uygulamalı Has the ability to analyze/interpret at the conceptual level to develop solutions to problems 5
PLO07 Beceriler - Bilişsel, Uygulamalı Collects/analyses data 5
PLO08 Bilgi - Kuramsal, Olgusal Interprets the results analyzed with the model 5
PLO09 Beceriler - Bilişsel, Uygulamalı Combines the information obtained from different sources within the framework of academic rules in a field which does not research
PLO10 Beceriler - Bilişsel, Uygulamalı It develops traditional approaches, practices and methods into new working methods when it deems necessary 3
PLO11 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team
PLO12 Yetkinlikler - Öğrenme Yetkinliği In addition to herself/himself professional development, constantly improves in scientific, cultural, artistic and social fields in line with interests and abilities
PLO13 Yetkinlikler - Öğrenme Yetkinliği Being aware of the necessity of lifelong learning, it follows the current developments in the field / constantly renews itself 2
PLO14 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research
PLO15 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses Turkish and at least one other foreign language, academically and in the business context 4
PLO16 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
PLO17 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on current economic and social issues 3
PLO18 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values


Week Plan

Week Topic Preparation Methods
1 Chapter 1: A Review of Basic Concepts: Concepts of statistics, data, population, sample, parameter, estimation, estimator Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
2 Chapter 1: A Review of Basic Concepts: Qualitative and quantitative data; The normal probability distirbution; Sampling distirbutions and central limit theorem Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
3 Chapter 2: Introduction to Regression Analysis: Modeling a response, Overiew of regression analysis Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
4 Chapter 3: Simple Linear Regression Model: The method of least squares, model assumptions Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
5 Chapter 3: Simple Linear Regression Model: An estimator of the variance, making inferences about the slope Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
6 Chapter 3: Simple Linear Regression Model: the coefficient of correlation, the coefficient of determination, using the model for estimation and prediction. Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
7 Chapter 3: Simple Linear Regression Model: Regression through the origin Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
8 Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav
9 Chapter 4: Multiple Linear Regression Model: General form of a multiple regression model, model assumptions, model fitting of a first-order multiple regression model with quantitative regressors Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
10 Chapter 4: Multiple Linear Regression Model: Estimation of the error variance, inferences about the parameters Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
11 Chapter 4: Multiple Linear Regression Model: The multiple coefficient of determination, The analysis of variance, F test Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
12 Chapter 4: Multiple Linear Regression Model: More complex multiple regression models Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
13 Chapter 4: Multiple Linear Regression Model: Using the model for estimation and prediction, A test for comparing nested models Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
14 Chapter 5:Model Building Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
15 Chapter 6: Variable screening methods Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme
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: 08.05.2024 12:32