ISB402 Stochastic Processes

4 ECTS - 3-0 Duration (T+A)- 8. Semester- 3 National Credit

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

Update Time: 03.05.2023 12:03