Details - Tematika

Economic mathematics II. (MATUBAN-ECOMATH2-1)

Basic data

Name and type of the study programme

Tourism and catering, undergraduate program

Curriculum

2024

Classes / consultation hours

2 + 2 + 0 (L+S+Labs)

Credits

5 credits

Theory – Practice

Theory: %, Practice: %

Recommended semester

Semester 2

Study mode

full-time

Prerequisites

Evaluation type

Colloquium

Course category

Compulsory

Language

English

Instructors

Responsible instructor

Körmöczi Koppány István

Responsible department

Gazdaságtudományi Kar

Instructor(s)

Dobjánné Dr. Antal Elvira Mercédesz

Checked by

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Course objectives

The aim of the course is to familiarize students with the basic concepts and methods of higher mathematics (linear algebra, linear programming, multivariable functions) and to provide them with the basic knowledge necessary for further study of mathematical methods to support economic decisions.

Course content

Lectures

1. Introduction to linear algebra. Solving systems of linear equations. Gauss-Jordan method. 2. Economic problems leading to systems of linear equations. Linear and quadratic interpolation. 3. Concepts of matrices, multiplication, inverse and rank of matrices. Determinant. Definition of eigenvalue, eigenvector, solution of simple problems. 4. Economic applications of matrices, matrix inverse, eigenvalue, eigenvector. Matrix of total and direct expenditure. Leontief's economic model. 5. Basic concepts of linear programming. Standard form. Graphical solution of bivariate linear programming problems. 6. Solution of linear programming problems using simplex method. Basic solutions. Solving textual linear programming problems. 7. Duality in linear programming. Solving a minimum problem using the simplex method. Solving textual problems. 8. Concept of a transportation problem, solving it with a distribution table. Vogel-Korda method for determining the initial program. 9. Solving a transportation problem with a fictitious station. Finding an alternative optimum. 10. Definition of bivariate functions, level lines, domain, limits, partial derivatives. 11. Extrema of bivariate functions, solving economic problems leading to the determination of the extrema of a bivariate function. 12. Concepts of multivariate functions, partial derivatives, Hessian matrix, global and local extrema.

Seminars

In the seminar, students solve tasks related to the topic of the lecture of the given week.

Acquired competences

Knowledge

Knowledge: Knowledge of the general and specific mathematical and scientific principles, rules, relationships and procedures necessary for the study of economics. Skills: The students are able to identify a higher mathematical problem, the method to be used to solve it, and then, on the basis of the method chosen, to solve it quickly and accurately. In the case of practical problems, they are able to construct and select the mathematical model needed to solve the problem, and to generalise the problem in the case of similar problems. Attitude: Have the stamina and tolerance of monotony to carry out practical activities. Autonomy and responsibility: Ability to work efficiently, qualitatively and continuously, to work independently and in cooperation with others, and to take responsibility for the work submitted. The students should take notes of the lectures and seminars, read the referred chapters of the recommended book, and solve the exercises to practice problem solving.

Skills

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Attitude

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Autonomy and responsibilities

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Requirements, evaluation and grading

Mid-term study requirements

Students should take notes of the lectures and seminars, read the referred chapters of the recommended book, and solve the exercises to practice problem solving. Attendance at seminars is mandatory. (You may miss up to 4 seminars.) The exam grade is calculated based on two midterm 20-point tests (March 24 and May 12, 2026), solving homework assignments worth a total of 20 points, and a 40-point exam. Students must achieve at least 20 points from midterm tests and 10 points from the homework assignments to qualify for the final exam. A make-up test will be offered during the final seminar, allowing students to retake one or two midterm tests to improve their point total and meet the eligibility requirement. The new points will replace the original score(s) from the retaken midterm test(s).

Exam requirements

Assessment thresholds (in accordance with the study and exam regulations): 86 - 100% performance: excellent (5) 76 - 85% performance: good (4) 61 - 75% performance: satisfactory (3) 50 - 60% performance: pass (2) - 49% performance: fail (1)

Generative AI usage

1st position: The use of GAI tools is not permitted when solving tasks. This means that GAI tools cannot be used when creating or solving formative or summative assessment elements, and the use of generative AI constitutes academic misconduct. The use of AI tools for language and spelling checking is not subject to the complete ban under the 1st position.

Study aids, laboratory background

Lecture notes of the instructor (uploaded to the Teams group of the lecture).

Readings

Compulsory readings

Knut Sydsaeter, Peter Hammond, Arne Strom, Andrés Carvajal: Essential Mathematics for Economic Analysis. 6th edition, Pearson, 2022