PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
BIO 648	NUMERICAL TAXONOMY	3 + 0	2nd Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	What is the numerical taxonomy? The purpose of numerical taxonomy, qualitative and quantitative characters, PCA, OTU concept, Clustering analysis: UPGMA, Array analysis, Discriminant analysis, applications of numerical taxonomy, Comparison of numerical taxonomy with other taxonomic methods
Course Content
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

COURSE'S CONTRIBUTION TO PROGRAM

Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	7	98
Assignments	1	5	5
Mid-terms	1	15	15
Final examination	1	35	35
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

Select Year

Course Details

Course Code	Course Title	L+P Hour	Course Code	Language Of Instruction	Course Semester
BIO 648	NUMERICAL TAXONOMY	3 + 0	1	Turkish	2023-2024 Fall

Course Coordinator	E-Mail	Phone Number	Course Location	Attendance
Asts. Prof. Dr. GÜRÇAY KIVANÇ AKYILDIZ	gkakyildiz@pau.edu.tr		FEN A0112	%

Goals		What is the numerical taxonomy? The purpose of numerical taxonomy, qualitative and quantitative characters, PCA, OTU concept, Clustering analysis: UPGMA, Array analysis, Discriminant analysis, applications of numerical taxonomy, Comparison of numerical taxonomy with other taxonomic methods
Content

Topics

Weeks	Topics
1	Definition, purpose and principles of Numerical taxonomy
2	Numerical (quantitative) characters
3	Non-numerical (qualitative) characters
4	OTU (Operational Taxonomic Unit) concept
5	The creation of the data matrices
6	Clustering analysis
7	Ordination analysis
8	Discriminant analysis
9	Applications of numerical taxonomy in plant systematic-I
10	Applications of numerical taxonomy in plant systematic-II
11	Midterm exam
12	Applications of numerical taxonomy in plant systematic-III
13	Numerical methods for complex taxonomic groups
14	Comparison of numerical taxonomy with other taxonomic methods

Materials

Materials are not specified.

Resources

Course Assessment

Assesment Methods	Percentage (%)	Assesment Methods Title
Final Exam	50	Final Exam
Midterm Exam	50	Midterm Exam

L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

Prospective Student