TÜRKÇE
ENGLISH
Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB423 |
| Name | Multivariate Statistical Analysis |
| Term | 2020-2021 Academic Year |
| Semester | 7. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 5 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | C Compulsory |
| Mode of study | Uzaktan Öğretim |
| Catalog Information Coordinator | Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY |
| Course Instructor |
Prof. Dr. GÜLESEN ÜSTÜNDAĞ ŞİRAY
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The goal is to construct the necessary theoretical background for multivariate statistical analysis.
Course Content
The content of this course is basic concepts of multivariate statistics, multivariate normal distribution, testing hypothesis about the multivariate data.
Course Precondition
Yok
Resources
Notes
1234
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learn the basic concepts of multivariate statistics. |
| LO02 | Explain the purpose of using of multivariate statistics. |
| LO03 | Determine the mean vector, variance-covariance and correlation matrices for multivariate data. |
| LO04 | Learn the probability density function, marginal probability density function, conditional distribution and statistical independency for multivariate distributions. |
| LO05 | Find the moment generating function for multivariate normal distribution. |
| LO06 | Find marginal probability density function, conditional probability density function for multivariate normal distribution. |
| LO07 | Make the parameter estimates for multivariate normal distribution. |
| LO08 | Test the hypothesis about the multivariate data. |
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 | 5 |
| PLO02 | - | Emphasize the importance of Statistics in life | 4 |
| 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 | 2 |
| PLO05 | - | Use proper methods and techniques to gather and/or to arrange the data | 5 |
| PLO06 | - | Utilize computer systems and softwares | 4 |
| PLO07 | - | Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events | 4 |
| PLO08 | - | Apply the statistical analyze methods | 4 |
| PLO09 | - | Make statistical inference(estimation, hypothesis tests etc.) | 5 |
| PLO10 | - | Generate solutions for the problems in other disciplines by using statistical techniques | 5 |
| 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 | 4 |
| PLO13 | - | Distinguish the difference between the statistical methods | 4 |
| 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 | 0 |
| 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 | 0 |
| PLO18 | - | Develop scientific and ethical values in the fields of statistics-and scientific data collection | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Basic concepts of multivariate statistics | Source reading | |
| 2 | Matrix theory for multivariate statistical analysis | Source reading | |
| 3 | Matrix theory for multivariate statistical analysis | Source reading | |
| 4 | Mean vector, variance-covariance matrix, correlation matrix | Source reading | |
| 5 | Probability density function, marginal probability density function, conditional distribution and statistical independency for multivariate distributions | Source reading | |
| 6 | Probability density function, characteristic functions, moments, moment generating function and parameter estimates | Source reading | |
| 7 | Maximum likelihood estimators for population parameters | Source reading | |
| 8 | Mid-Term Exam | Review the topics discussed in the lecture notes and sources. | |
| 9 | Marginal normal distribution, conditional normal distribution | Source reading | |
| 10 | Distribution of linear relations, independency of subvector variables | Source reading | |
| 11 | Obtaining the parameters given the density function | Source reading | |
| 12 | Multivariate test methods (likelihood ratio test) | Source reading | |
| 13 | Multivariate test methods (composition-intersection test) | Source reading | |
| 14 | Test on mean vectors | Source reading | |
| 15 | Test on covariance matrices, Testing hypothesis with statistical package programs. | Source reading | |
| 16 | Term Exams | Review the topics discussed in the lecture notes and sources. | |
| 17 | Term Exams | Review the topics discussed in the lecture notes and sources. |
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 | 12 | 12 |
| Final Exam | 1 | 18 | 18 |
| Total Workload (Hour) | 114 | ||
| Total Workload / 25 (h) | 4,56 | ||
| ECTS | 5 ECTS | ||