COURSE INFORMATION Course Title: MATH. FOR ECONOMICS AND BUSINESS II

Code	Course Type	Regular Semester	Theory	Practice	Lab	Credits	ECTS
BUS 102	A	2	4	0	0	4	5

Academic staff member responsible for the design of the course syllabus (name, surname, academic title/scientific degree, email address and signature)	NA
Main Course Lecturer (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	M.Sc. Sidorela Meta smeta@epoka.edu.al , Monday 8:45-10:30, Thursday 9:45-11:30 (E-206)
Second Course Lecturer(s) (name, surname, academic title/scientific degree, email address and signature) and Office Hours:	NA
Teaching Assistant(s) and Office Hours:	NA
Language:	English
Compulsory/Elective:	Compulsory
Study program: (the study for which this course is offered)	Bachelor in Business Informatics (3 years)
Classroom and Meeting Time:	Wednesday 11:45-13:30 (E/213) & Friday 8:45-10:30 (E 212)
Code of Ethics:	Code of Ethics of EPOKA University Regulation of EPOKA University "On Student Discipline"
Attendance Requirement:	75 %
Course Description:	Mathematics for Economics and Business II: Limits and Continuity. Average Rate of Change and Slope. Derivatives, Instantaneous Rate of Change, Higher Order Derivatives. Optimization, Concavity of Inflection Points. Maxima and Minima. Revenue, Cost and Profit Applications, Anti Derivatives, Rules of Integration, Differential Equations, Mathematics of Finance, Simple and Compound Interest, Present Value, Effective Interest, Future Value, Annuities.
Course Objectives:	The aim of this course is to give the basic ingredients of mathematics for business and economics. Namely, functions, derivatives and differentials. Moreover, most of the models in economics appear in the form of linear models.

BASIC CONCEPTS OF THE COURSE

1	Slope, tangent.
2	First-order derivative and second-order derivative of a function with one variable.
3	Marginal functions, stationary points, maximum, minimum, elasticity.
4	Partial derivative and second-order partial derivative of a function with two variables.
5	Maximum and minimum points of a function with two variables.
6	Integration.
7	Methods of integration.
8	Matrix. Inverse matrix. Cramer's rule. Gauss-Jordan elimination method.
9	Linear problems.
10	Differential equations.

COURSE OUTLINE

Week	Topics
1	Differentiation & marginal functions. Chapter 4: an introduction to the basic idea of differentiation, derivative of power functions, rules of differentiation and economic applications in marginal functions. (Pages 268 - 327)
2	Optimisation & elasticity. Chapter 4 (continue): standard economic applications of differentiation in elasticity and optimisation, derivative of the exponential and natural logarithm functions (Pages 329 - 371)
3	Partial elasticity. Chapter 5: functions of some variables, partial elasticity and marginal functions, first and second-order partial derivatives of functions of two variables, the application of partial derivatives in economics. (Pages 390 - 418)
4	Revision. Exercises. Quiz 1.
5	Unconstrained & Constraint Optimisation. Chapter 5 (continue): application of first and second-order partial derivatives of functions of two variables in unconstrained and constrained optimisation, Lagrange multipliers (Pages 433 - 470)
6	Review. Exercises.
7	Midterm Exam
8	Indefinite integration. Definite integration. Chapter 6: integration of functions of one variable, methods of integration, area surface under the graph of a function, producer’s and consumer’s surpluses (Pages 484 - 508)
9	Basic matrix operations. Matrix inversion. Chapter 7: matrix operations of addition, subtraction and multiplication, determinant and inverse of a matrix (Pages 524 - 540)
10	Cramer`s rule. Gauss-Jordan elimination method. Chapter 7 (continue): Cramer’s rule for solving systems of linear equations (Pages 545 - 573)
11	Revision. Exercises. Quiz 2.
12	Graphical solution of linear programming problems. Chapter 8: basic mathematical techniques and special cases when problems have either no solution or infinitely many solutions, economic problem as a linear programming problem (Pages 586 - 614)
13	Differential equations. Chapter 9: the complementary function of a difference equation, the particular solution of a difference equation, the complementary function of a differential equation, the particular solution of a differential equation (Pages 627 - 651)
14	Review. Exercises.

Prerequisite(s):	Math. for Economics and Business I
Textbook(s):	Ian Jacques, Mathematics for Economics and Business, Pearson ninth edition 2018
Additional Literature:	E. F. Haeussler, Jr. and R. S. Paul (1999) Introductory Mathematical Analysis, Perentice-Hall Inc. New Jersey.
Laboratory Work:	NA
Computer Usage:	NA
Others:	No

COURSE LEARNING OUTCOMES

1	Estimate the derivative of a function by measuring the slope of a tangent.
2	Derive the relationship between marginal and average revenue
3	Differentiate complicated functions using a combination of rules.
4	Determine the price elasticity for general linear demand functions.
5	Use the first and the second-order derivative to find maximum and minimum points of a function with one variable.
6	Perform implicit differentiation.
7	Use the first and the second-order derivative to find maximum and minimum points of a function with two variables.
8	Use the method of Lagrange multipliers to solve constrained optimisation problems.
9	Use methods of integration to calculate the consumer’s surplus, producer’s surplus.
10	Use matrix inverses to solve systems of linear equations arising in economics.

COURSE CONTRIBUTION TO... PROGRAM COMPETENCIES (Blank : no contribution, 1: least contribution ... 5: highest contribution)

No	Program Competencies	Cont.
Bachelor in Business Informatics (3 years) Program
1	Identify activities, tasks, and skills in management, marketing, accounting, finance, and economics.	5
2	Apply key theories to practical problems within the global business context.	5
3	Demonstrate ethical, social, and legal responsibilities in organizations.	5
4	Develop an open minded-attitude through continuous learning and team-work.	4
5	Integrate different skills and approaches to be used in decision making and data management.	1
6	Combine computer skills with managerial skills, in the analysis of large amounts of data.	1
7	Provide solutions to complex information technology problems.	1
8	Recognize, analyze, and suggest various types of information-communication systems/services that are encountered in everyday life and in the business world.	1

COURSE EVALUATION METHOD

Method	Quantity	Percentage
Midterm Exam(s)	1	30
Quiz	2	10
Final Exam	1	50
	Total Percent:	100%

ECTS (ALLOCATED BASED ON STUDENT WORKLOAD)

Activities	Quantity	Duration(Hours)	Total Workload(Hours)
Course Duration (Including the exam week: 16x Total course hours)	16	4	64
Hours for off-the-classroom study (Pre-study, practice)	16	2	32
Mid-terms	1	10	10
Assignments			0
Final examination	1	15	15
Other	4	1	4
Total Work Load:			125
Total Work Load/25(h):			5
ECTS Credit of the Course:			5

CONCLUDING REMARKS BY THE COURSE LECTURER

I do not tolerate cheating, or any type of academic dishonesty. If caught, student will immediately receive a failing grade.