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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS EMT 1006 LINEAR ALGEBRA COMPULSORY 3 0 0 4

Offered By

Econometrics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR ALI KEMAL ŞEHIRLIOĞLU

Offered to

Econometrics (Evening) Econometrics

Course Objective

The main objective of the course is to give the student definiton of vector, determinant, matrix and explaining how to use them with mathematics analysis method in multi dimension space.

Learning Outcomes of the Course Unit

1   To be able to express definitons of eigenvalue and eigenvector. 2   To be able to describe vector, determinant, matrix 3   To be able to describe linear algebras methods which can be used to solve inter-disciplines problems. 4   To be able to solve multi variety linear equation systems. 5   To be able to relate problems with linear algebras.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Vectors and vectorial operations 2 Scaler and vectorial multiplication 3 Linear depency and indepency of vectors 4 Determinants definition, properties. 5 Minors, signed minors and special determinants 6 Minors, signed minors and special determinants 7 Matrix definition, matrix operations 8 Matrix properties and special matrix 9 Matrix properties and special matrix 10 Mid-term 11 Matrix rank, rows and columns operations, reverse of square matrix. 12 Solvings of linear equation systems 13 Solvings of homogen linear equation systems. 14 Eigenvalue and eigenvectors 15 Diagonalisation, Cayley-Hamilton theorem

Recomended or Required Reading

1- LINEAR ALGEBRA & IT S APPLICATIONS (DAVID C.LAY) 2- MATRIX THEORY WITH APPLICATIONS (JACK L.GOLDBERG) 3- MATRIX ALGEBRA USEFUL FOR STATISTICS (SHAYLE R.SEARLE)

Planned Learning Activities and Teaching Methods

This course will be presented using class lectures, class discussions, overhead projections, and demonstrations.

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 2 24 Preparation for midterm exam 1 15 15 Preparation for final exam 1 20 20 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 97

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