ISB507 Theory of Linear Models-I

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

Information

Code ISB507
Name Theory of Linear Models-I
Term 2024-2025 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 Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. SADULLAH SAKALLIOĞLU


Course Goal / Objective

The objective of this course is to discuss different methods used in the simple/multiple lineer regression models.

Course Content

Multivariate normal distribution; distribution of quadratic forms; Paremeter estimation and hypothesis testing in simple linear regression; Properties of least squares estimator and geometry of least squares, Maximum likelihood estimators and its properties; Estimation, testing and coefficient of determination in multivariate normal distribution; Related topics in linear models.

Course Precondition

no

Resources

Linear Models Alvin C. Rencher John Wiley 2000

Notes

Linear Models S.R.Searle John Wiley 1971


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Knowledge and understanding multivariate normal distribution and distribution of quadratic forms,
LO02 To understand the basic logic of simple lineer regression(SLR)
LO03 Perform parameter estimation and confidence interval
LO04 Perform hypothesis testing for SLR model
LO05 To learn parameter estimation and confidence interval for multiple linear regression(MLR),
LO06 To know properties of least squares estimator and geometry of least squares
LO07 To learn maximum likelihood estimators and its properties,
LO08 To learn testing in multivariate normal regression


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Develops new methods and strategies in modeling statistical problems and generating problem-specific solutions. 3
PLO02 Bilgi - Kuramsal, Olgusal Can do detailed research on a specific subject in the field of statistics. 3
PLO03 Bilgi - Kuramsal, Olgusal Have a good command of statistical theory to contribute to the statistical literature.
PLO04 Bilgi - Kuramsal, Olgusal Can use the knowledge gained in the field of statistics in interdisciplinary studies. 2
PLO05 Yetkinlikler - Öğrenme Yetkinliği Can organize projects and events in the field of statistics. 3
PLO06 Yetkinlikler - Öğrenme Yetkinliği Can perform the stages of creating a project, executing it and reporting the results. 2
PLO07 Beceriler - Bilişsel, Uygulamalı Have the ability of scientific analysis. 2
PLO08 Bilgi - Kuramsal, Olgusal Can produce scientific publications in the field of statistics. 3
PLO09 Bilgi - Kuramsal, Olgusal Have analytical thinking skills.
PLO10 Yetkinlikler - Öğrenme Yetkinliği Can follow professional innovations and developments both at national and international level.
PLO11 Yetkinlikler - Öğrenme Yetkinliği Can follow statistical literature. 3
PLO12 Beceriler - Bilişsel, Uygulamalı Can improve his/her foreign language knowledge at the level of making publications and presentations in a foreign language.
PLO13 Bilgi - Kuramsal, Olgusal Can use information technologies at an advanced level.
PLO14 Bilgi - Kuramsal, Olgusal Have the ability to work individually and make independent decisions.
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have the qualities necessary for teamwork.
PLO16 Bilgi - Kuramsal, Olgusal Have a sense of professional and ethical responsibility. 2
PLO17 Bilgi - Kuramsal, Olgusal Acts in accordance with scientific ethical rules. 3


Week Plan

Week Topic Preparation Methods
1 Multivariate normal distribution reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Distribution of quadratic forms reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
3 Estimation, hypothesis test and confidence interval reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Multiple regression reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Least squares estimator and its properties reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 The model in centered form reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
7 Maximum likelihood estimators and its properties reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Review the topics discussed in the lecture notes and references Ölçme Yöntemleri:
Yazılı Sınav, Ödev
9 Generalized least squares reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 General linear hypothesis tests reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Confidence region and confidence interval reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
12 Simultaneous intervals reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
13 Estimation in multivariate normal regression reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 Testing in multivariate normal regression reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Tests and confidence interval for coefficient of determination reading, examination of literature Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
16 Term Exams Review the topics discussed in the lecture notes and references Ölçme Yöntemleri:
Yazılı Sınav, Ödev
17 Term Exams Review the topics discussed in the lecture notes and references 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: 09.05.2024 02:16