Course Information

Course Information
Course Title Code Language Type Semester L+U Hour Credits ECTS
. PEM004 Turkish Compulsory 1. Semester 2 + 2 3.0 3.0
Prerequisite Courses
Course Level Undergraduate
Mode of delivery face to face
Course Coordinator Prof. Dr. Aybike Ayfer KARADAĞ
Instructor(s)
Goals In the Research and Experimental Methods course, which is the second level after the Statistics course, various experimental designs are explained with examples, and these methods are used to prepare the obtained data for analysis and interpret the analysis results. Course Objectives and Goals: Through all learning activities conducted within the scope of this course during the semester, the following are targeted: - To instill the notion of research in students, - To develop analytical thinking, - To increase their ability to make interpretations by providing examples from various branches of agriculture.
Course Content Principles of planning, organizing, and conducting experiments, Experimental Error, Repetition and method, Duncan test, Sample problem solutions and interpretation of results, Prerequisites for variance analysis, Randomized Block Design, Latin Square Design, Sample problem solutions and interpretation of results, Factorial Experiments, Interaction concept, Simple and main effects, Factorial Experiments in Randomized Plots, Sample problem solutions and interpretation of results, Sample problem solutions and interpretation of results, Arrangement of Factorial Experiments in Randomized Blocks, Analysis of data obtained from Randomized Block Factorial Experiments, Blocks, Split-Plot Design, Nested Groups Design, Sample problem solutions and interpretation of results, Repeated Measures Experiments, Single-Factor Repeated Measured Experiments, Sample problem solutions and interpretation of results, Concept of Model and Variance Components, Sample problem solutions and interpretation of results
Learning Outcomes
# Öğrenme Kazanımı
1 Be able to understand research idea and it’s important in development
2 Be able to know on principles of developing and research
3 Be able to earn skill on planning of research projects and their evaluation on the base national and international
4 Be able to select suitable experimental design in order to increase truth degree in experiment
5 Be able to measure and observe the characters according to statistical principles
6 Be able to select suitable experimental design according to purpose of research
7 Be able to earn skill on conducte of trials in good health and niceness
8 Be able to earn skill on right and objective deciding
Lesson Plan (Weekly Topics)
Week Topics/Applications Method
1. Week Definition of the experiment, its objectives, and its organization
2. Week F distribution variance analysis technique randomized block experimental design
3. Week multiple comparison methods Preparation, After Class Study
4. Week multiple comparison methods Preparation, After Class Study
5. Week random blocks and Latin square test layout Preparation, After Class Study
6. Week crandom blocks and Latin square test layout Preparation, After Class Study
7. Week FACTORIAL EXPERIMENTS Preparation, After Class Study
8. Week FACTORIAL EXPERIMENTS Preparation, After Class Study
9. Week FACTORIAL EXPERIMENTS Preparation, After Class Study
10. Week Randomized Block Design with Split Plots Preparation, After Class Study
11. Week Randomized Block Design with Split Plots Preparation, After Class Study
12. Week REPEATED MEASURED TESTS Preparation, After Class Study
13. Week REPEATED MEASURED TESTS Preparation, After Class Study
14. Week THE CONCEPT OF MODEL AND EXPECTED ELEMENTS OF SQUARE MEANS Preparation, After Class Study
*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 Knowledge: Within the framework of environmental and social sustainability principles (considering the public interest and value), to have the knowledge and understanding to gain and reflect up-to-date information that will carry out planning, design, management activities and research,
2 Knowledge: To have knowledge in planning and design approaches regarding sustainable resource management, healthy living and access to food, resilience, climate change management, rural / urban development and use of technology,
3 Knowledge: To have knowledge about universal, corporate and professional ethical values related to the field,
4 Knowledge: To have knowledge of national and international norms, conventions, professional principles, laws, regulations and standards related to the field,
5 Skill: The ability to use the necessary tools for the holistic perception, planning, design and creation of management models of processes within the landscape in the context of spatial / temporal scale, in the effects, pressures and changes faced by the inhabited geography,
6 Skill: The ability to develop alternative constructions and solutions in accordance with field-specific theories and methods in planning and design processes,
7 Skill: The ability to take responsibility in an interdisciplinary / transdisciplinary team, to set goals in a collaborative and inclusive manner, to plan tasks and to work in a participatory manner,
8 Skill: The ability to discuss individual views on field-specific issues and to improve oneself
9 Competence: Competence to act with the awareness of lifelong learning and research by internalizing sustainable, innovative and entrepreneurial approaches,
10 Competence: Competence of foreign language skills at a level to communicate and follow the developments in the field,
12 Competence: Competence to prepare, implement, manage and monitor projects about the field, taking into account of knowledge in Landscape Architecture theory and methodology, open green space planning, green and blue infrastructure, management, protection and interpretation of cultural landscapes and landscape management,
13 Competence: Competence to produce projects in interdisciplinary collaborations in landscape planning, design and materials with the experience of tree nursery, application and office internship by integrating knowledge on the management of landscapes of different scales, planning and design of infrastructure projects, material and construction techniques with information technologies in the field,
Relations with Education Attainment Program Course Competencies
Program Requirements DK1 DK2 DK3 DK4 DK5 DK6 DK7 DK8
PY1 0 0 0 0 0 0 0 0
PY2 0 0 0 0 0 0 0 0
PY3 0 0 0 0 0 0 0 0
PY4 0 0 0 0 0 0 0 0
PY5 0 0 0 0 0 0 0 0
PY6 0 0 0 0 0 0 0 0
PY7 1 1 1 1 1 1 1 1
PY8 0 0 0 0 0 0 0 0
PY9 0 0 0 0 0 0 0 0
PY10 0 0 0 0 0 0 0 0
PY12 0 0 0 0 0 0 0 0
PY13 0 0 0 0 0 0 0 0
Recommended Sources
Ders Kitabı veya Notu Ders Kitabı veya Ders Notu bulunmamaktadır.
Diğer Kaynaklar
  • 1. Orhan DÜZGÜNEŞ, Tahsin KESİCİ ve Fikret GÜRBÜZ (1993). İstatistik Metotları (2. Baskı), Ankara Üniversitesi, Ziraat Fakültesi yayınları: 1291, Ders Kitabı: 369. 2. Fikret GÜRBÜZ; Ensar BAŞPINAR, M. MUHİP ÖZKAN, Mehmet MENDEŞ, Sıdık KESKİN ve Handan ÇAMDEVİREN (2000). İstatistik Metotları Dersi Uygulama Kılavuzu, Ankara Üniversitesi, ziraat Fakültesi, Eğitim, Araştırma ve Geliştirme Vakfı Yayınları No:7 3. Fikret GÜRBÜZ, Ensar BAŞPINAR ve Zahide KOCABAŞ (1995). Araştırma ve Deneme Metodları Uygulama Kılavuzu (II. Baskı). Ankara Üniversitesi, Ziraat fakültesi, Yayın No: 1431, Uygulama Kılavuzu: 244. 4. Orhan DÜZGÜNEŞ, Tahsin KESİCİ, Orhan KAVUNCU ve Fikret GÜRBÜZ (1987). Araştırma ve Deneme Metodları (istatistik Metodları-II). Ankara Üniversitesi, Ziraat fakültesi Yayınları:1021, Ders Kitabı: 295. 5. SNEDECOR, W. and COCHRAN W. G. 1980. Statistical Methods. Seventh Edition. The Iowa state University Press, Ames, Iowa, USA. 6. ZAR, J.H. 1999. Biostatistical Analysis. Fourth Ed., Prentice Hall Upper Saddle River, New Jersey, 07458. 7. WINNER, B. J., BROWN, R. B. And MICHELS K. M. 1991. Statistical Principles in Experimental design. Third Edition. McGraw Hill, Inc., USA
ECTS credits and course workload
ECTS credits and course workload Quantity Duration (Hour) Total Workload (Hour)
Ders İçi
Class Hours 14 4 56
Ders Dışı
Preparation, After Class Study 10 0.4 4
Research 1 4 4
Presentation (Preparation) 10 0.2 2
Practice 10 0.4 4
Other Activities 1 2 2
Sınavlar
Midterm 1 2 2
Final 1 2.5 2.5
Total Workload 76.5
*AKTS = (Total Workload) / 25,5 ECTS Credit of the Course 3.0