ISB402 Stochastic Processes

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

Information

Unit FACULTY OF SCIENCE AND LETTERS
STATISTICS PR.
Code ISB402
Name Stochastic Processes
Term 2017-2018 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
Label C Compulsory
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. SELAHATTİN KAÇIRANLAR
Course Instructor Prof. Dr. DENİZ ÜNAL ÖZPALAMUTCU (Bahar) (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

Resources

Notes



Course Learning Outcomes

Order Course Learning Outcomes
LO01 Explains the subject of linear modelling.
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 Distinguish between chi-square distribution, t-distribution and F-distribution.
LO05 Distinguishes the independence of quadratic forms.
LO06 Students who attend this course will have the expectation and variances of quadratic forms
LO07 Explains 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 Statistics
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 programs and builds models, solves problems, does analyses and comments about problems concerning randomization
PLO07 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 3
PLO08 Bilgi - Kuramsal, Olgusal Make statistical inference (estimation, hypothesis tests etc.) 4
PLO09 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques and gain insight 3
PLO10 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programs
PLO11 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods
PLO12 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods
PLO13 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually
PLO14 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
PLO15 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
2 orthogonal matrices literature review
3 inverse of matrices literature review
4 Chi square distribution, t-distribution, F distribuiton, literature review
5 Chi square distribution, t-distribution, F distribuiton, literature review
6 independence of quadratic forms literature review
7 expectation and variances of quadratic forms literature review
8 Mid-Term Exam literature review
9 full rank models literature review
10 matrices for full rank models literature review
11 estimation for full rank models literature review
12 full rank models literature review
13 full rank models, confidence intervals literature review
14 regression coefficients for full rank models literature review
15 regression coefficients for full rank models literature review
16 Term Exams literature review
17 Term Exams literature review


Assessment (Exam) Methods and Criteria

Assessment Type Midterm / Year Impact End of Term / End of Year Impact
1. Midterm Exam 100 40
General Assessment
Midterm / Year Total 100 40
1. Final Exam - 60
Grand Total - 100


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: 29.04.2025 02:19