COURSE UNIT TITLE

: COMPUTER ASSISTED DESIGN AND ANALYSIS OF EXPERIMENTS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ENV 5060 COMPUTER ASSISTED DESIGN AND ANALYSIS OF EXPERIMENTS 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 ILGI KARAPINAR

Offered to

Ph.D. in Biotechnology
Environmental Engineering
Ph.D. in Biotechnology
ENVIRONMENTAL ENGINEERING
BIOTECHNOLOGY

Course Objective

The main objective of the course is to introduce the computer programs used in statistical design of experiments, analysis of the data and evaluation of results. The theoretical background of statistical experimental design methods, basic principles of performing the experiments, and the statistical methods used in the analysis of the data are discussed in the contents of course

Learning Outcomes of the Course Unit

1   Define the statistical methods used in experimental designes
2   Select the design method according to number of factor or number of experiment
3   Solve the statistical experimental design methods used for decreasing number of experiment
4   Associtae the statiscal design methods for optimization of a process
5   Practice the use of software for statistical anlaysis of experimental design methods.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 General Factorial Design Theoretical background Design and analysis on Design expert 7.0
2 2k Factorial Design Min. Run Resolution IV Min. Run. Resulotion V Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
3 Fractional Factorial Design 2k-p Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
4 Other Factorial Design Methods Theoretical Background o Taguchi experimental design o Pluckett Burman Experimental Design o D-Optimal Design Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
5 Response Surface Method and Designs Theoretical Background on o Box-Wilson experimental design o Central composite design o Box Behnken experimental design Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
6 Mixed Experimental Design Methods Theoretical Background on o Simplex Lattice o Simplex Centroid o User Specified o D-optimal Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
7 Mixed Experimental Design Methods Theoretical Background on o Simplex Lattice o Simplex Centroid o User Specified o D-optimal Design and analysis on Design expert 7.0 Design and analysis on Statistica 9.0
8 Method Validation Repeatibility Reproducibility Analysis on Statistica 9.0
9 Method Validation Repeatibility Reproducibility Analysis on Statistica 9.0
10 Measurement of uncertainity Theoretical background Fish-bone analyses Sources of uncertainities Uncertainity calculations on Excell
11 Measurement of uncertainity Theoretical background Fish-bone analyses Sources of uncertainities Uncertainity calculations on Excell
12 Measurement of uncertainity Theoretical background Fish-bone analyses Sources of uncertainities Uncertainity calculations on Excell
13 Measurement of uncertainity Theoretical background Fish-bone analyses Sources of uncertainities Uncertainity calculations on Excell
14 Examples from literature

Recomended or Required Reading

II. TEXTBOOK: Montgomery, D. C. , Design and Analysis of Experiments, Jhon Willey and Sons, 1996.

III. REFERENCE BOOKS:
George E. P. BOX ,Norman R. DRAPER, Experimental Design,Response Surfaces,1987
Box, G.E.P, Hunter J.S., Hunter, W.G., Statistics for Experimenters; An Introduction to Design, Data Analysis and Model Development , Jhon Willy & Sons , 1978.
Michael, S.L. Experimental Design and Methods. London Sage Publication, 1993
Hinkelmann, K., Kempthorne,O. Design and Analysis of Experiments: Introduction to Experimental Design, Jhon Willey and Sons, 1994

Planned Learning Activities and Teaching Methods

The course is taught in a lecture by the aid of computer. Statistical design methods, data entry, ststistical analysis methdos will be presented to the students on compouter. The studenst could use their own conmputers simultaneously. All class members are expected to attend.

Assessment Methods

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


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria



Language of Instruction

English

Course Policies and Rules

Students should have intermediate level of statistic knowledege. Studenst have to prepare homeworks after each statistical experimental design method was discussed in the class. The homeworks have to be preapred on computer by using statistical softwares.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparations before/after weekly lectures 10 3 30
Preparing assignments 10 7 70
Preparation for final exam 1 10 10
Final 1 10 10
TOTAL WORKLOAD (hours) 148

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.15445
LO.2455
LO.3545
LO.44545
LO.555

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

Copyright 2015 DEÜ. BİD

HOME / ABOUT US / DEGREE PROGRAMMES / GENERAL INFORMATION FOR STUDENTS / INTERNATIONAL RELATIONS