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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 2010 BASICS OF VARIANCE ANALYSIS ELECTIVE 3 0 0 5

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR IPEK DEVECI KOCAKOÇ

Offered to

Econometrics Econometrics

Course Objective

The DOE and analysis of variance approach can economically satisfy the needs of problem solving and product/process design optimization projects. By learning and applying this technique, engineers, scientists, and researchers can significantly reduce the time required for experimental investigations.

Learning Outcomes of the Course Unit

1   1. Understand the importance of analysis of variance 2   2. Learn the experimental designs most widely used in practice 3   3. Choose an appropriate experimental design based on the study objectives 4   4. Construct and implement the design selected 5   5. Analyse the data collected based on the design used and its underlying assumptions 6   6. Interpret the results of the experiment and report the conclusions

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction 2 Simple Comparative Experiments 3 Experiments with a Single Factor 4 Randomized Blocks, Latin Squares and Related Designs 5 Incomplete Block Design 6 Factorial Design 7 Midterm 8 Rules for Sums of Squares and Expected Mean Squares 9 The 2k Factorial Design 10 Two-Level Fractional Designs 11 Some Other Topics Regarding Factorial and Fractional Factorial Designs 12 Nested or Hierarchial Design 13 Multifactor Experiments with Randomization Restrictions 14 Final Exam

Recomended or Required Reading

Design And Analysis of Experiments-3rd Ed., Douglas C.Montgomery , John Wiley and Sons(1991)

Planned Learning Activities and Teaching Methods

Explaining Method, Q-A Method, Argument Method and Problem Solving Method

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 MTEG MIDTERM GRADE MTEG * 1 3 FIN FINAL EXAM 4 FCGR FINAL COURSE GRADE MTEG * 0.40 + FIN * 0.60 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTEG * 0.40 + RST * 0.60 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

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 12 3 36 Preparations before/after weekly lectures 12 3 36 Preparation for midterm exam 1 20 20 Preparation for final exam 1 20 20 Preparing assignments 4 1 4 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 118

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 1 1 LO.2 1 1 LO.3 1 1 LO.4 1 1 LO.5 1 1 LO.6 1 1