GENERAL MATHEMATICS II

TBF122

Course Code: TBF122
Semester: Second Term (Spring)
Theory+Practice: 3 + 0
ECTS: 6

Course Type

Compulsory Course

Course Level

Bachelor's Degree

Year of Study

Semester

Second Term (Spring)

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Develop the ability to define and solve linear equation systems, creating matrix representations of them.
Gain the ability to perform operations on matrices using the Gauss-Jordan elimination method and obtain solutions to the systems.
Enhance the ability to understand the concept of determinants and solve linear equation systems using Cramer's rule.
Acquire the ability to define multivariable functions, calculate partial derivatives, and determine the maximum and minimum points of these functions.
Improve the skill of solving optimization problems by applying the least squares method and the Lagrange multipliers method.
Gain the ability to recognize linear inequalities, formulate linear programming problems, and solve constrained maximization and minimization problems using the simplex method.

Mode of Delivery

Face to face

Prerequisites

Recommended Optional Programme Components

None

Course Description

This course covers fundamental topics such as matrices, systems of linear equations, and determinants. The course also includes techniques like the Leontief method, linear inequalities, linear programming, the simplex method, minimization and maximization problems, multivariable functions, partial derivatives, maximum-minimum problems, Lagrange multipliers, and the least squares method.

Course Contents

WEEK	TOPICS
1^st Week	Linear equation systems and matrices
2^nd Week	The Gauss-Jordan elimination method
3^rd Week	Matrix operations, inverse matrix
4^th Week	Determinants, Cramer's rule, and Leontief's input-output analysis
5^th Week	Multivariable functions and partial derivatives
6^th Week	Maximum and minimum in multivariable functions
7^th Week	Least squares method, Lagrange multiplier method, their applications
8^th Week	Midterm exam
9^th Week	Linear inequalities
10^th Week	Linear programming
11^th Week	Introduction to the simplex method, constrained maximization problems
12^th Week	Constrained minimization problems
13^th Week	Mixed constrained maximization and minimization, the Big M method, and their applications
14^th Week	Mixed constrained maximization and minimization, the Big M method, and their applications

Recommended or Required Reading

a) Internet: The primary resource for this course is the material available at www.baskent.edu.tr/~karakas. This material is also available as an open course on the Başkent University Open Course Materials portal at http://moodle.midas.baskent.edu.tr/course/view.php?id=318.

b) Books: The following books are available in our university library:

Barnett, R. A., Zeigler, M. R., & Byleen, K. E. (2008). Calculus for business, economics, life sciences, and social sciences. Prentice Hall.

Budnick, F. S. (1993). Applied mathematics for business, economics, and social sciences. McGraw-Hill.

Adams, R. A. (2003). Calculus: A complete course. Addison-Wesley, Longman.

Thomas, G. B., & Finney, R. L. (1990). Calculus and analytic geometry. Addison-Wesley Publishing.

Stewart, J. (1995). Calculus. Brooks/Cole Publishing.

Edwards, C. H., Jr., & Penney, D. E. (1986). Calculus and analytic geometry. Prentice Hall.

Planned Learning Activities and Teaching Methods

Lecture
Discussion
Questions/Answers

Assessment Methods and Criteria

	Quantity	Percentage (%)
Mid-term	1	30
Quiz	6	16
Attendance	1	4
Total(%)		50
Contribution of In-term Studies to Overall Grade(%)		50
Contribution of Final Examination to Overall Grade(%)		50
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam	1	1	1
Preparation for Quiz	6	4	24
Individual or group work	14	3	42
Preparation for Final exam	1	40	40
Course hours	14	3	42
Preparation for Midterm exam	1	30	30
Laboratory (including preparation)
Final exam	1	1	1
Homework
Total Work Load			180
Total Work Load / 30 (h)			6
ECTS Credit of the Course			6

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5	LO6
K1
K2
K3
K4	X	X	X	X		X
K5
K6			X	X	X
K7
K8			X	X	X	X
K9
K10
K11
K12