Description of Individual Course Units
Course Unit CodeCourse Unit TitleType of Course UnitYear of StudySemesterNumber of ECTS Credits
9102015312004Experimental Design in HorticultureCompulsory118
Level of Course Unit
Second Cycle
Objectives of the Course
The aim of this course is to give the students the ability to design experiments, collect data and understand the approaches in data analysis, and interpret the results in horticulture.
Name of Lecturer(s)
Assoc. Prof. Dr. Özlem TUNCAY
Learning Outcomes
1The ability to collect data with the necessary precision
2The ability to interpret the analysis results
3The ability to design experiments in horticultural production and breeding
4The ability to analyze collected data
Mode of Delivery
Face to Face
Prerequisites and co-requisities
None
Recommended Optional Programme Components
None
Course Contents
Precision and accuracy of data, normal distribution, establishment of hypotesis and testing, analysis of variance, mean comparisons Simple and multifactorial experimental designs, relationships between variables, analysis of counts.
Weekly Detailed Course Contents
WeekTheoreticalPracticeLaboratory
0Data accuracy and precision Normal distribution Testing of normality Assisted problem solving
1Transformations Hypotheses testing Assisted problem solving
2Designing experiments in horticulture, and important principles Analysis of Variance (ANOVA) Assisted problem solving
3Mean comparisons (LSD, Duncan, Tukey)Assisted problem solving
4The Completely Randomized DesignAssisted problem solving
5The Randomized Complete Block DesignAssisted problem solving
6Mid-term examAssisted problem solving
7The Latin Square DesignAssisted problem solving
8Orthogonal ComparisonsAssisted problem solving
9Factorial Experiments; Completeley Randomized DesignAssisted problem solving
10Factorial Experiments: The Randomized Complete Block Design Assisted problem solving
11The Split-Plot DesignAssisted problem solving
12The Split-Split-Plot Design Assisted problem solving
13Relationships between variables Assisted problem solving
14Analysis of Counts. Chi-SquareAssisted problem solving Practise exam
15Final Exam
Recommended or Required Reading
1. Püskülcü, H., İkiz, F., Eren, Ş. 2006. İstatistiğe Giriş. Barış Yayınları, Fakülteler Kitabevi, İzmir. 2. Düzgüneş, O.; Kesici, T.; Kavuncu, O.; Gürbüz, F. 1987. Araştırma ve Deneme Metotları. Ankara Üniversitesi Ziraat Fakültesi Yayınları: 1021, Ders Kitabı: 295, Ankara. 3. Little, T.M.; Hills, F.J., 1972. Statistical Methods in Agricultural Research. University of California. 4. Bek, Y., Efe, E., 1989. Araştırma ve Deneme Metodları. Çukurova Üniversitesi, Ziraat Fakültesi Ders Kitabı, No: 71, Adana.
Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"
Assessment Methods and Criteria
Term (or Year) Learning ActivitiesQuantityWeight
SUM0
End Of Term (or Year) Learning ActivitiesQuantityWeight
SUM0
SUM0
Language of Instruction
Turkish
Work Placement(s)
None
Workload Calculation
ActivitiesNumberTime (hours)Total Work Load (hours)
Midterm Examination13030
Final Examination14040
Attending Lectures14228
Problem Solving14228
Individual Study for Mid term Examination14040
Individual Study for Final Examination15050
Laboratory Examination14228
Oral Examination7214
TOTAL WORKLOAD (hours)258
Contribution of Learning Outcomes to Programme Outcomes
PO
1
PO
2
PO
3
PO
4
PO
5
PO
6
PO
7
PO
8
LO1   455  
LO2   532  
LO3   533  
LO4        
* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High
 
Ege University, Bornova - İzmir / TURKEY • Phone: +90 232 311 10 10 • e-mail: intrec@mail.ege.edu.tr