
Description of Individual Course UnitsCourse Unit Code  Course Unit Title  Type of Course Unit  Year of Study  Semester  Number of ECTS Credits  İST206  MATRIX THEORY AND STATISTICS APPLICATIONS  Compulsory  2  4  5 
 Level of Course Unit  First Cycle  Objectives of the Course  To understand the definition of matrix, its types and properties, to solve systems of equations with matrix approach, to express some statistical information with matrices and to show its application with package programs.  Name of Lecturer(s)  Doç.Dr. Halil TANIL  Learning Outcomes  1  To be able to understand matrix definition, types and operations.  2  To be able to solve systems of linear equations with matrix approach.  3  To be able to express some statistical information with matrices and to calculate mean, variancecovariance  4  To be able to make matrix applications with computer programs. 
 Mode of Delivery  Face to Face  Prerequisites and corequisities   Recommended Optional Programme Components   Course Contents  Definition and types of matrices, addition and multiplication in matrices, transpose of matrix, inverse of matrix and MoorePenrose inverse, fragmentation of matrices, determinant, linear independence, vector spaces, rank concept, solution of linear equation systems with matrices, eigenvalues and eigenvectors, inner product and Hermian matrices matrix representations of some statistical information, least squares method, sample mean with matrix operations, covariance and correlation calculation, mean and variance of linear combinations of random variables, etc. topics.  Weekly Detailed Course Contents  
1  Definition and types of matrix  Introduction to Matlab   2  Addition and multiplication in matrices, transpose of matrix  Matlab applications   3  Inverse of the matrix, MoorePenrose inverse  Matlab applications   4  Fragmentation of matrices  Matlab applications   5  Determinant  Matlab applications   6  Linear independence, vector spaces  Matlab applications   7  Rank concept  Matlab applications   8  Midterm    9  Solution of linear equation systems with matrices  Matlab applications   10  Solution of linear equation systems with matrices  Matlab applications   11  Eigenvalues and eigenvectors, inner product and Hermitian matrices  Matlab applications   12  Matrix representations of some statistical information  Matlab applications   13  Least squares method  Matlab applications   14  Sample mean, covariance and correlation by matrix operations  Matlab applications   15  Mean and variance of linear combinations of random variables  Matlab applications   16  Final exam   
 Recommended or Required Reading   Planned Learning Activities and Teaching Methods   Assessment Methods and Criteria   Language of Instruction  Turkish  Work Placement(s)  
 Workload Calculation 

Midterm Examination  1  2  2  Final Examination  1  2  2  Attending Lectures  14  3  42  Practice  14  1  14  Individual Study for Homework Problems  1  6  6  Individual Study for Mid term Examination  3  10  30  Individual Study for Final Examination  4  10  40  
Contribution of Learning Outcomes to Programme Outcomes  LO1  4  4  4   4   4    5    4  4   4   5       4  LO2  4  5  4   4   4    5    4  4   4   5       4  LO3  5  5  4   4   5    5    4  4   4   5       4  LO4  4  4  4   4   5    5    4  4   5   5       4 
 * Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High 



Ege University, Bornova  İzmir / TURKEY • Phone: +90 232 311 10 10 • email: intrec@mail.ege.edu.tr 
