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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BYM 0535 STATISTICAL ANALYSIS IN BIOENGINEERING STUDIES ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR NURI AZBAR

Offered to

Industrial Ph.D. Program In Advanced Biomedical Technologies

Course Objective

It is aimed to teach the followings; basics of statistical analysis; experimental design and optimization techniques

Learning Outcomes of the Course Unit

1   Learning of advanced experimental design methods 2   Optimization by advanced statistical methods

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Basic Statistics 2 Basic Statistics 3 Basic Statistics 4 Basic Statistics 5 Experimental Design (Box-Wilson) 6 Experimental Design (Box-Wilson) 7 Experimental Design (Box-Wilson) 8 Mid-term Exam 9 Experimental Design (Box-Behnken) 10 Experimental Design (Box-Behnken) 11 Experimental Design (Box-Behnken) 12 Experimental Design (Box-Behnken) 13 Experimental Design (Optimization by Tagucchi Method) 14 Project Presentations

Recomended or Required Reading

Prof. Dr. Kadir Sümbüloğlu, Doç.Dr. Vildan Sümbüloğlu: Biyoistatistik, ISBN:975-7527-12-2 - Softwares Planned Learning Activities and Teaching Methods

Planned Learning Activities and Teaching Methods

midterm %40 final %60

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FIN FINAL EXAM 3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60

Further Notes About Assessment Methods

to be announced.

Assessment Criteria

to be announced.

Language of Instruction

Turkish

Course Policies and Rules

to be announced.

Contact Details for the Lecturer(s)

Prof. Dr. Nuri AZBAR

Office Hours

to be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 10 140 Preparation for midterm exam 1 30 30 Preparation for final exam 1 25 25 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 199

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 LO.1 4 3 LO.2 5 4 4