COURSE UNIT TITLE

: MULTIVARIATE STATICAL ANALYSIS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
BYL 5074 MULTIVARIATE STATICAL ANALYSIS ELECTIVE 3 0 0 6

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR FERHAT MATUR

Offered to

Ph.D. in Biology
Biology

Course Objective

Phase of analyzing the data which graduate student obtained during the studies difficult to pass.Intended to correct the deficiencies of students during analysis phase and intended to transfer to students new multivariate analysis which is used

Learning Outcomes of the Course Unit

1   To know statical methods for scientfic studies
2   Be able to execute data analysis
3   To evaluate statical results
4   To choose proper statical analysis
5   To know multivariate statical analysis suhc as canonical corelation, Factor analysis, clustering analysis, discriminant function analysis, principal component analysis.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Basic concepts
2 ANOVA
3 MANOVA
4 Correlation and Regression
5 Correlation and Regression
6 Correlation and Regression
7 Function Analysis of decomposition
8 Midterm Exam
9 Factor Analysis
10 Factor Analysis
11 Essential Elements of Analysis
12 Cluster Analysis
13 Correspondence analysis
14 Final exam

Recomended or Required Reading

Grimm, L.G., Yarnold, P.R. 1995. Reading and understanding multivariate statistics. American Psychological Association (APA)
Kachigan, S.K. 1991. Multivariate statistical Analysis: A conceptual introduction. Radius Press. Grimm, L.G., Yarnold, P.R. 1995. Reading and understanding multivariate statistics. American Psychological Association (APA)

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. All class members are expected to attend and both the lecture and take part in the discussion sessions. Besides the taught lecture, group presentations are to be prepared by the groups assigned for that week and presented to open a discussion session.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 +ASG * 0.20 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


Further Notes About Assessment Methods

None

Assessment Criteria

Student will be evaluated with midterm exams, homework presentation and final exam.

Language of Instruction

Turkish

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy

Contact Details for the Lecturer(s)

ferhat.matur@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 14 14
Preparation for final exam 1 14 14
Preparation for quiz etc. 4 3 12
Preparing assignments 14 2 28
Preparing presentations 6 2 12
Midterm 1 2 2
Final 1 2 2
Quiz etc. 4 1 4
TOTAL WORKLOAD (hours) 158

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.145555555
LO.25555555
LO.355555
LO.45555555
LO.545555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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