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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| ZOOTECHNICS (MASTER) (WITH THESIS) | |
| Code | ZO695 |
| Name | Multivariate Statistical Analysis |
| Term | 2026-2027 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi Melis ÇELİK GÜNEY |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim is to teach the importance of multivariate statistical analyses and to determine which type of multivariate method should be applied to which type of data. It also aims to equip students with the ability to examine relationships among different variables, perform data reduction, apply classification and modeling techniques, and interpret the results for use in decision-making processes.
Course Content
Basic concepts related to multivariate data analysis methods, data preprocessing, multiple regression analysis, canonical correlation analysis, logistic regression analysis, factor analysis, cluster analysis, and discriminant analysis.
Course Precondition
There are no prerequisites for this course.
Resources
Lecture notes prepared by the instructor. Alpar, Reha, 2011. Multivariate Statistical Methods. Detay Publishing, Ankara.
Notes
Course textbooks = Multivariate statistics.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explains the basic concepts of multivariate statistical analysis. |
| LO02 | Defines multivariate data sets and performs preliminary analyses. |
| LO03 | Performs multiple regression analysis, canonical correlation analysis, and logistic regression analysis. |
| LO04 | Performs factor analysis, cluster analysis, and discriminant analysis. |
| LO05 | Selects and applies the appropriate statistical method. |
| LO06 | Interprets and reports the results of the analysis. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | After undergraduate education, increases knowledge in one of the fields of animal breeding and breeding, feeds and animal nutrition, biometrics and genetics. | 5 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Understands the interaction between different disciplines | 3 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Gains the ability to develop strategic approaches and produce regional, national or international solutions for the field of animal science | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Zootekni bilimindeki verileri kullanarak bilimsel yöntemlerle bilgiyi geliştirebilme, bilimsel, toplumsal ve etik sorumluluk bilinci ile bu bilgileri kullanabilme becerisini kazanır | 5 |
| PLO05 | Bilgi - Kuramsal, Olgusal | Gains the ability to use and develop information technologies with computer software and hardware knowledge required by the field of animal science. | 4 |
| PLO06 | Bilgi - Kuramsal, Olgusal | Gains the ability to convey their own studies or current developments in the field of animal science to groups in the field or other fields of science, verbally and visually. | 3 |
| PLO07 | Bilgi - Kuramsal, Olgusal | Gains the ability to evaluate the quality processes of animal products | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Gains the ability to keep animal production dynamic in accordance with changing economic and social conditions. | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Gains the ability to follow national and international current issues, to follow developments in lifelong learning, science and technology, to constantly renew themselves and to transfer innovations to animal production. | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Absorbs the relationship between animal products and human health and community welfare |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Content of multivariate data analysis. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 2 | Basic concepts related to multivariate statistical analysis methods. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 3 | Examination of the dataset, graphical representation, and descriptive statistics. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 4 | Problems that may be encountered in datasets. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma |
| 5 | Multiple regression analysis. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 6 | Canonical correlation analysis. | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 7 | Logistic regression analysis | An internet search related to the topic will be recommended by the instructor | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 8 | Mid-Term Exam | An internet search related to the topic will be recommended by the instructor | Ölçme Yöntemleri: Ödev, Yazılı Sınav |
| 9 | Factor analysis 1 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 10 | Factor analysis 2 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 11 | Discriminant analysis 1 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 12 | Discriminant analysis 2 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 13 | Cluster analysis 1 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 14 | Cluster analysis 2 | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 15 | Analyses of different datasets | An internet search related to the topic will be recommended by the instructor. | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Tartışma, Alıştırma ve Uygulama |
| 16 | Term Exams | An internet search related to the topic will be recommended by the instructor. | Ölçme Yöntemleri: Yazılı Sınav |
| 17 | Term Exams | An internet search related to the topic will be recommended by the instructor. | 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 | 2 | 30 | 60 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 2 | 2 |
| Final Exam | 1 | 2 | 2 |
| Total Workload (Hour) | 148 | ||
| Total Workload / 25 (h) | 5,92 | ||
| ECTS | 6 ECTS | ||