CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Linear Algebra İST201 FALL 3+0 C 5
    Learning Outcomes
    1-Acquire vectors and vector spaces.
    2-Learns matrix definition and properties.
    3-Does matrix operations.
    4-Calculates determinant and takes matrix inverse.
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14342
    Assignments0000
    Short-Term Exams (exam + preparation) 2011010
    Midterm exams (exam + preparation)3012020
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 5013030
    Other 0000
    Total Workload (hours)   144
    Total Workload (hours) / 30 (s)     4,8 ---- (5)
    ECTS Credit   5
  • Course Content
  • Week Topics Study Metarials
    1 Introduction to Algebra and Predictions; Vector space concept and operations in vectors. Lecture Note
    2 Space vectors and Sub vector space; Linear dependence and independence of vectors. Lecture Note
    3 Definition and properties of matrices; Addition, multiplication and subtraction operations in matrices. Lecture Note
    4 Determinants and calculation methods; Matrix inversion and calculation methods. Lecture Note
    5 Linear transformations, definition and properties; A matrix of linear transformation. Lecture Note
    6 Relation to rank and matrices of a linear transformation; Rank of a matrix. Lecture Note
    7 Linear equation systems and solution methods. Lecture Note
    8 Linear equation systems and solution methods. Lecture Note
    9 Solution of linear equation systems with determinants and inverse matrix and Gaussian elimination method. Lecture Note
    10 Statistical applications in the solution of linear equation systems. Lecture Note
    11 Matrix Polynomials and Characteristic function. Lecture Note
    12 Finding Eigen-values and Eigen-vectors and diagonalization. Lecture Note
    13 Calculation of high-order strength of the matrices. Lecture Note
    14 Application of general statistics with matrices. Lecture Note
    Prerequisites -
    Language of Instruction Turkish
    Responsible Dr. Öğr. Üyesi Tuba KOÇ
    Instructors -
    Assistants -
    Resources Hacısalihoğlu, H. H. (1991). Lineer Cebir Teori ve Uygulamaları, İkinci Baskı çeviri, Ankara: Nobel Dağ. Ltd. Şti.
    Supplementary Book -Sabuncuoğlu, A. (2004). Lineer Cebir. Ankara: Nobel Dağ. Ltd. Şti. - Dost, S. (1978). Teori ve Problemlerle Lineer Cebir. Birinci Baskı Çeviri, Ankara: Güven Kitabevi Yayınları. - Anton, H. (1984). Elemantary Linear Algebra, New York: John Wiley & Sons. - Akın, Ö. (2002). Uygulamalı Lineer Cebir. 7?inci Baskıdan Çeviri. Ankara: Palme Yayın Dağ. Paz
    Goals To gain the ability to extend these skills to statistical applications by establishing a relationship between matrices and systems of linear equations. Thus, basic knowledge about linear algebra which the student will need during undergraduate and graduate education. In addition, it will be possible to understand how to solve the problems that are encountered.
    Content Introduction to Algebra and Predictions, Vector space concept and operations in vectors, Space vectors and Sub vector space, Linear dependence of vectors and independence, Definition and properties of matrices, Matrix Operations, Matrix Types, Finding the nth power of the matrix, Matrix Decision and Inverse, Linear transformations, A matrix of linear transformation, The rank of a matrix, Linear equation systems and solution methods, Apply statistical solutions to linear equation systems, Matrix Polynomials and Characteristic function, Self-values and self-vectors, Diagonalizable transformation operations, Application of general statistics with matrices
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 To have informations about conceptional, theoretical and applied statistics and and associates the concepts with each other. -
    2 To collect, save and arrange the statistical data, builds the proper tables and graphics to summarize data -
    3 To analyse the data, to able to determine suitable statistical method, to make more efficient inferences and forecasts for the future 1
    4 To design and analyse an experiment and interpreting the results -
    5 To have the knowlegde about Mathematics and Economics 3
    6 To define statistics problems and develop suggestions by using statistical survey. -
    7 To use the profiency knowlegde on interdiscipliner studies 2
    8 To have the ability of planing, managing and reporting of a project -
    9 To use computer softwares and programmes for statistics methods. 1
    10 To have the ability of analythical thinking 3
    11 To have the individual study skills and be capable of independent decision-making 4
    12 To have the qualifications required for team work -
    13 To follow developments in statistics field by using a foreign language and can be connected with their colleagues. 3
    14 To have scientific and ethnical values in data collection and interpretation in statistics dicipline. 2
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