          Description of Individual Course Units
 Course 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, variance-covariance 4 To be able to make matrix applications with computer programs.
Mode of Delivery
Face to Face
Prerequisites and co-requisities
Recommended Optional Programme Components
Course Contents
Definition and types of matrices, addition and multiplication in matrices, transpose of matrix, inverse of matrix and Moore-Penrose 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
 Week Theoretical Practice Laboratory 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, Moore-Penrose 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
Planned Learning Activities and Teaching Methods
Assessment Methods and Criteria
 Term (or Year) Learning Activities Quantity Weight SUM 0 End Of Term (or Year) Learning Activities Quantity Weight SUM 0 SUM 0
Language of Instruction
Turkish
Work Placement(s) 