TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB402 |
| Name | Stochastic Processes |
| Term | 2018-2019 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. SELAHATTİN KAÇIRANLAR
(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 | 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 | Students who attend this course will have the expectation and variances of quadratic forms |
| LO08 | Students who attend this course will have the regression coefficients for full rank models |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics | 2 |
| PLO02 | - | Emphasize the importance of Statistics in life | 3 |
| PLO03 | - | Define basic principles and concepts in the field of Law and Economics | 0 |
| PLO04 | - | Produce numeric and statistical solutions in order to overcome the problems | 4 |
| PLO05 | - | Use proper methods and techniques to gather and/or to arrange the data | 0 |
| PLO06 | - | Utilize computer systems and softwares | 0 |
| PLO07 | - | Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events | 5 |
| PLO08 | - | Apply the statistical analyze methods | 1 |
| PLO09 | - | Make statistical inference(estimation, hypothesis tests etc.) | 3 |
| PLO10 | - | Generate solutions for the problems in other disciplines by using statistical techniques | 4 |
| PLO11 | - | Discover the visual, database and web programming techniques and posses the ability of writing programme | 0 |
| PLO12 | - | Construct a model and analyze it by using statistical packages | 3 |
| PLO13 | - | Distinguish the difference between the statistical methods | 5 |
| PLO14 | - | Be aware of the interaction between the disciplines related to statistics | 5 |
| PLO15 | - | Make oral and visual presentation for the results of statistical methods | 5 |
| PLO16 | - | Have capability on effective and productive work in a group and individually | 5 |
| PLO17 | - | 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 | 5 |
| PLO18 | - | Develop scientific and ethical values in the fields of statistics-and scientific data collection | 5 |
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 | ||