Course Information

Course Information
Course Title Code Language Type Semester L+U Hour Credits ECTS
Research and Experimental Methods ZFZ302 Turkish Compulsory 6. Semester 2 + 1 3.0 3.0
Prerequisite Courses
Course Level Undergraduate
Mode of delivery Face to face
Course Coordinator
Instructor(s)
Goals This course is to provide basic knowledge of the subjects covered by Research and Trial Methods to undergraduate students and to provide students with basic information / concepts about the courses they will take during their undergraduate studies.
Course Content Introduction to variance analysis, It's all about chance, The randomized blocks trial plan, Latin square trial plan, Factorial arrangements, Divided parcel trial plan Repeated experiments Orthogonal comparisons Correlation and regression analysis Non parametrik Tests
Learning Outcomes
# Öğrenme Kazanımı
1 Basic knowledge on Research and Trying Methods is acquired.
2 Methods of setting up a trial pattern are learned
3 the relations between statistics and research are learned.
Lesson Plan (Weekly Topics)
Week Topics/Applications Method
1. Week Introduction to variance analysis, Interview Presentation (Preparation)
2. Week Trying pattern which is all about chance, Interview Presentation (Preparation)
3. Week The randomized blocks in trying plan, Interview Presentation (Preparation)
4. Week Latin square triying plan, Presentation (Preparation) Interview
5. Week Factorial arrangements, Interview Presentation (Preparation)
6. Week Divided pattern trying plan Interview Presentation (Preparation)
7. Week Divided pattern trying plan Interview Presentation (Preparation)
8. Week Midterm Class Hours
9. Week Repeated experiments Interview Presentation (Preparation)
10. Week Orthogonal comparisons Presentation (Preparation) Interview
11. Week Orthogonal comparisons Interview Presentation (Preparation)
12. Week Correlation and regression analysis Presentation (Preparation) Interview
13. Week Correlation and regression analysis Interview Presentation (Preparation)
14. Week Non parametric Tests Presentation (Preparation) Interview
*Midterm and final exam dates are not specified in the 14-week course operation plan. Midterm and final exam dates are held on the dates specified in the academic calendar with the decision of the University Senate.
The Matrix for Course & Program Learning Outcomes
No Program Requirements Level of Contribution
1 2 3 4 5
1 Utilizes (or Applies) knowledge of natural sciences and mathematics in developing various processes in their field.
2 Demonstrates adherence (or behaves) to ethical and deontological principles in decision-making and implementation processes.
3 Utilizes (or Applies) scientific and technological developments in the applications within their field.
4 Integrates (or Combines) fundamental engineering knowledge with technical tools to solve engineering problems in their field using an analytical approach.
5 Designs all technical systems, system components, and production processes relevant to their field.
6 Implements (or Applies) plant and animal production processes in accordance with scientific and technical principles.
7 Utilizes (or Employs) data-driven core technologies in agricultural production processes.
8 Applies (or Implements) sustainability principles and approaches to agricultural processes.
9 Utilizes (or Applies) managerial and institutional knowledge related to agriculture, while considering (or observing) global and local developments.
10 Manages soil and water resources and agricultural waste sustainably by integrating scientifically based irrigation, drainage, and soil conservation systems with precision agriculture and digital water management technologies.
11 Designs agricultural machinery and equipment for agricultural production and post-harvest processes, evaluates their performance, and enhances their efficiency through automation.
Relations with Education Attainment Program Course Competencies
Program Requirements DK1 DK2 DK3
PY1 4 4 4
PY2 4 4 4
PY3 5 5 5
PY4 5 5 5
PY5 4 4 4
PY6 3 3 3
PY7 4 4 4
PY8 4 4 4
PY9 4 4 4
PY10 4 4 4
PY11 3 3 3
Recommended Sources
Ders Kitabı veya Notu Ders Kitabı veya Ders Notu bulunmamaktadır.
Diğer Kaynaklar
  • 1) Seyidoğlu, H., Bilimsel Araştırma ve Yazma El Kitabı, Güzem Can Yayınları, İstanbul, 2009. 2) Özdamar, K., Modern Bilimsel Arastırma Yöntemleri, Kaan Kitabevi, 2004. 3) Dinler, Z., Bilimsel Araştırma ve Internet’e Bağlı Bilgi Merkezleri El Kitabı, Bursa, 1997. 4) Serper, Ö. ve Gürsakal, N., Araştırma Yöntemleri, Filiz Kitapevi, İstanbul, 1989.
ECTS credits and course workload
ECTS credits and course workload Quantity Duration (Hour) Total Workload (Hour)
Sınavlar
Midterm 1 1 10 10
Final 1 10.5 10.5
Classroom Activities 14 4 56
Total Workload 76.5
*AKTS = (Total Workload) / 25,5 ECTS Credit of the Course 3.0