Information
Code | ISB402 |
Name | Stochastic Processes |
Term | 2023-2024 Academic Year |
Semester | 8. Semester |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 4 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. SELAHATTİN KAÇIRANLAR |
Course Instructor |
Prof. Dr. SELAHATTİN KAÇIRANLAR
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
to give the basis of Linear and statistical models
Course Content
to give the basis of Linear and statistical 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 | Students who attend this course will have the capability of linear models |
LO02 | Students who attend this course will have the capability of estimation |
LO03 | Students who attend this course will have the capability of statistical inference |
LO04 | Students who attend this course will have the Chi square distribution, t-distribution, F distribuiton, |
LO05 | Students who attend this course will have the independence of quadratic forms |
LO06 | Students who attend this course will have the expectation and variances of quadratic forms |
LO07 | Understands the issue of matrix representation of full-rank models, estimators of parameters in the model. |
LO08 | Students who attend this course will have create a common confidence region on the regression coefficients in full-rank models. |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics | |
PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | |
PLO03 | Bilgi - Kuramsal, Olgusal | Define basic principles and concepts in the field of Law and Economics | |
PLO04 | Bilgi - Kuramsal, Olgusal | Produce numeric and statistical solutions in order to overcome the problems | |
PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | 2 |
PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer systems and softwares | 2 |
PLO07 | Bilgi - Kuramsal, Olgusal | Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events | 3 |
PLO08 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 3 |
PLO09 | Bilgi - Kuramsal, Olgusal | Make statistical inference(estimation, hypothesis tests etc.) | 4 |
PLO10 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques | 3 |
PLO11 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programme | |
PLO12 | Bilgi - Kuramsal, Olgusal | Construct a model and analyze it by using statistical packages | 3 |
PLO13 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | |
PLO14 | Beceriler - Bilişsel, Uygulamalı | Be aware of the interaction between the disciplines related to statistics | 3 |
PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | |
PLO16 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | |
PLO17 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs | |
PLO18 | Yetkinlikler - Öğrenme Yetkinliği | Develop scientific and ethical values in the fields of statistics-and scientific data collection |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Matrix algebra | literature review | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
2 | orthogonal matrices | literature review | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
3 | eigenvalues and eigenvectors | literature review | Öğretim Yöntemleri: Anlatım |
4 | Chi square distribution, t-distribution | literature review | Öğretim Yöntemleri: Anlatım |
5 | F distribuiton | literature review | Öğretim Yöntemleri: Anlatım |
6 | independence of quadratic forms | literature review | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
7 | expectation and variances of quadratic forms | literature review | Öğretim Yöntemleri: Anlatım |
8 | Mid-Term Exam | literature review | Ölçme Yöntemleri: Yazılı Sınav |
9 | Matrix representation of full-rank models | literature review | Öğretim Yöntemleri: Anlatım |
10 | the estimator of model parameters | literature review | Öğretim Yöntemleri: Anlatım |
11 | Estimator of variance in full-rank models | literature review | Öğretim Yöntemleri: Anlatım |
12 | confidence intervals of estimators and their functions | literature review | Öğretim Yöntemleri: Anlatım |
13 | confidence intervals II | literature review | Öğretim Yöntemleri: Anlatım |
14 | Common confidence region on the regression coefficients in full-rank models | literature review | Öğretim Yöntemleri: Anlatım |
15 | Common confidence region II | literature review | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
16 | Term Exams | literature review | Ölçme Yöntemleri: Yazılı Sınav |
17 | Term Exams | literature review | 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 | 3 | 42 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 7 | 7 |
Final Exam | 1 | 18 | 18 |
Total Workload (Hour) | 109 | ||
Total Workload / 25 (h) | 4,36 | ||
ECTS | 4 ECTS |