EKMZ202 Regression Analysis

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

Information

Code EKMZ202
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 Türkçe
Level Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. GÜLSEN KIRAL
Course Instructor
1 2
Arş.Gör.Dr. Çiğdem KOŞAR TAŞ (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

There are no prerequisites.

Resources

Reha Alpar 2003. Uygulamalı Çok Değişkenli İstatistiksel Yöntemlere Giriş 1

Notes

1-Rawlings, John O.(1988). Applied Regression Analysis: A Research Tool, Wadsworth and Brooks. 2-Miller, I. and M. Miller (2004). Mathematical Statistics with Applications, Pearson Education.


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Defines concepts of statistics, data, population, sample, parameter, estimation, estimator.
LO02 Distinguish between quantitative and qualitative data.
LO03 Explain the Least Squares Method in the estimation of linear regression model.
LO04 Predicts the best fit model for the data.
LO05 It exemplifies the validity of the predicted model.
LO06 Performs the variance analysis.
LO07 Explains model assumptions.
LO08 Interprets hypothesis tests for model parameters.
LO09 Defines confidence intervals for model parameters.
LO10 Makes computer applications of the learned basic concepts.


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 1
PLO05 Beceriler - Bilişsel, Uygulamalı Models problems with Mathematics, Statistics, and Econometrics 3
PLO06 Beceriler - Bilişsel, Uygulamalı Has the ability to analyze/interpret at the conceptual level to develop solutions to problems 4
PLO07 Beceriler - Bilişsel, Uygulamalı Collects/analyses data 4
PLO08 Beceriler - Bilişsel, Uygulamalı 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 3
PLO10 Beceriler - Bilişsel, Uygulamalı It develops traditional approaches, practices and methods into new working methods when it deems necessary 2
PLO11 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Leads by taking responsibility individually and/or within the team 3
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 constantly renews itself by following the current developments in its field. 3
PLO14 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses a package program of Econometrics, Statistics, and Operation Research 5
PLO15 Yetkinlikler - İletişim ve Sosyal Yetkinlik Uses Turkish and at least one other foreign language, academically and in the business context
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 1
PLO17 Yetkinlikler - Alana Özgü Yetkinlik Interprets data on current economic and social issues
PLO18 Yetkinlikler - Alana Özgü Yetkinlik Applies social, scientific and professional ethical values 4


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, Tartışma
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, Tartışma, Alıştırma ve Uygulama
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, Tartışma, Alıştırma ve Uygulama
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, Tartışma
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, Tartışma, Alıştırma ve Uygulama
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, Tartışma, Alıştırma ve Uygulama
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
8 Mid-Term Exam Preparation for midterm 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, Tartışma, Alıştırma ve Uygulama
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, Tartışma, Alıştırma ve Uygulama
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, Tartışma, Alıştırma ve Uygulama
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
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, Tartışma, Alıştırma ve Uygulama
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, Tartışma
15 Chapter 6: Variable screening methods-Term Exams Students will be prepared by studying relevant subjects from source books according to the weekly program Öğretim Yöntemleri:
Soru-Cevap, Alıştırma ve Uygulama
16 Term Exams Preparation for final exam Ölçme Yöntemleri:
Yazılı Sınav, Ödev
17 Term Exams Preparation for final exam Ölçme Yöntemleri:
Yazılı Sınav, Ödev


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 11:37