Information
Code | ZO0028 |
Name | Non -parametric Statistical Analysis with R |
Term | 2024-2025 Academic Year |
Semester | . Semester |
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 |
Course Goal / Objective
This course aims to teach the Non-parametric statistical methods using with R
Course Content
Assumptions for parametrical tests, rank calculation methods, non-parametric tests for one and two samples, non-parametric tests for one-way and two-way data tables, factorial designs, non-parametric correlation and regression methods, randomization analysis,categorical data analysis
Course Precondition
At least, completing a bachelor level courses such as Introduction to Statistics or parametric statistical methods is required.
Resources
Cebeci, Z. (2019). Non-parametric Statistical Analysis with R. Abaküs Kitap, Istanbul. ISBN :9786052263600
Notes
Non-parametric Methods. http://www.r-tutor.com/elementary-statistics/non-parametric-methods
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Learns the differences between parametric and non-parametric statistics |
LO02 | Learns the non-parametric statistical methods. |
LO03 | Learns how to analyse the data with non-parametric statistical analysis using R |
LO04 | Analyzes the assumptions for the non-parametric methods. |
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. | 3 |
PLO02 | Bilgi - Kuramsal, Olgusal | Understands the interaction between different disciplines | 1 |
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 | |
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. | 5 |
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. | |
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 | Assumption for the parametric statistics | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
2 | Non-parametric methods for one sample data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
3 | Non-parametric methods for two samples data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
4 | Non-parametric methods for one-way data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
5 | Non-parametric methods for two-way data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
6 | Post-hoc tests (1) | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
7 | Post-hoc tests (2) | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
8 | Mid-Term Exam | Preparation for the exam | Ölçme Yöntemleri: Sözlü Sınav, Ödev |
9 | Non-parametric methods for analysing factorial design data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
10 | Non-parametric methods for correlation analysis | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
11 | Non-parametric regression analysis | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
12 | Logistic regression and classification | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
13 | Testing randomization (1) | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
14 | Testing randomization (2) | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
15 | Analysis of categorical data | Searching for the learning resources on the Internet, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. | Öğretim Yöntemleri: Anlatım, Soru-Cevap |
16 | Term Exams | Preparation for the exam | Ölçme Yöntemleri: Sözlü Sınav, Ödev |
17 | Term Exams | Preparation for the exam | Ölçme Yöntemleri: Ödev, Sözlü 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 | 5 | 70 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
Final Exam | 1 | 30 | 30 |
Total Workload (Hour) | 157 | ||
Total Workload / 25 (h) | 6,28 | ||
ECTS | 6 ECTS |