ZO0028 Non -parametric Statistical Analysis with R

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

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

Update Time: 13.05.2024 01:45