ZO656 Statistial Programming and Analysis with R

6 ECTS - 4-0 Duration (T+A)- . Semester- 4 National Credit

Information

Code ZO656
Name Statistial Programming and Analysis with R
Term 2024-2025 Academic Year
Semester . Semester
Duration (T+A) 4-0 (T-A) (17 Week)
ECTS 6 ECTS
National Credit 4 National Credit
Teaching Language Türkçe
Level Yüksek Lisans Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof. Dr. ZEYNEL CEBECİ


Course Goal / Objective

This course aims to teach the methods for statistical analysis, generating simple and advanced graphics, and statistical programming and applications with R..

Course Content

This course covers the basic statistical analysis, simple and advanced graphic plotting, and statistical programming and applications with R..

Course Precondition

No prerequisites

Resources

Cebeci, Z. (2019). Non-parametric Statistical Data Analysis with R. Abaküs Kitap, İstanbul. ISBN 9786052263600 Cebeci, Z. (2020). Veri Biliminde R İle Veri Önişleme. Nobel Akademik Yayıncılık, Ankara. ISBN 9786254060755

Notes

R Tutorial. https://www.tutorialspoint.com/r/index.htm


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Works in R statistical computing environment
LO02 Learns how to analyse data with R.
LO03 Learns the basic descriptive and inferential statistical methods.
LO04 Produces and interprets the graphical results.


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 2
PLO03 Bilgi - Kuramsal, Olgusal Gains the ability to develop strategic approaches and produce regional, national or international solutions for the field of animal science 1
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. 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 Installing and working with R On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
2 Data types and data organization with R On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
3 Introduction to statistical methods On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
4 Descriptive statistics On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
5 Probability and computation of probabilities On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
6 Probability distributions On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
7 Data visualization techniques On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
8 Mid-Term Exam Preparation for the exam Ölçme Yöntemleri:
Ödev, Sözlü Sınav
9 Comparsion of sample means On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
10 Comparison of proportions On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
11 Comparison of variances On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
12 Correlations and simple linear regression On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
13 Introduction to categorical data analysis On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
14 One-way ANOVA On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Alıştırma ve Uygulama
15 Case study On the Internet, searching for the learning resources, reading the tutorials, lecture notes and textbooks, and problem solving related with the topic. Öğretim Yöntemleri:
Gösterip Yaptırma
16 Term Exams Preparation for the exam Ölçme Yöntemleri:
Ödev, Sözlü Sınav
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 4 56
Out of Class Study (Preliminary Work, Practice) 14 4 56
Assesment Related Works
Homeworks, Projects, Others 0 0 0
Mid-term Exams (Written, Oral, etc.) 1 12 12
Final Exam 1 28 28
Total Workload (Hour) 152
Total Workload / 25 (h) 6,08
ECTS 6 ECTS

Update Time: 13.05.2024 01:45