Македонски (Macedonian)English (United Kingdom)

Quantitaive Methods for Business and Economics

The course is designed to meet the needs of those who already have a couple of years work experience in economics, finance, accounting, investments, marketing, insurance, production and ecology. It enables the participants to improve their basic skills in formulation and analysis of models and solution of the problems in many business situations. Moreover the candidates learn not only to identify the appropriate statistical methods and to apply them to practical problems, but they also get sense to critically analyze the situation.

QUANTITATIVE METHODS FOR BUSINESS AND ECONOMICS
 
WHO ATTENDS THIS COURSE?

The course is designed to meet the needs of those who already have a couple of years work experience in economics, finance, accounting, investments, marketing, insurance, production and ecology. It enables the participants to improve their basic skills in formulation and analysis of models and solution of the problems in many business situations. Moreover the candidates learn not only to identify the appropriate statistical methods and to apply them to practical problems, but they also get sense to critically analyze the situation.

COURSE TOPICS

The participants are trained to:
  • Project cash flow and make planning decisions in the present, based on the accurate calculation of cash flow projections
  • Calculate present and future values of payments and annuities.
  • Apply the advanced economic theory analysis covering utility function demand function, production function and optimization behaviour, cost function, revenue function and profit maximization, price determination under perfect competition.
  • Explore the static and dynamic optimization which is the basis of the modern economic theory
  • Use the descriptive statistics in tabular and graphic formats.
  • Understand the laws of probability.
  • Describe and use discrete and continuous probability distributions.
  • Develop skills at sampling and construct sampling distributions.
  • Use the statistical methods in interval estimation and hypothesis testing.
  • Deal with portfolios of financial assets such as stocks and bonds.
  • Understand the statistical process control methods and the decision making support they provide for quality control and quality improvement.
  • Work with large–scale forecasting models in predicting major macroeconomic variables such as GDP, inflation, employment and interest rates.

PARTICIPANT EXERCISES

Participants develop their skills in this course by:
  • Interactive lectures and workshops Numerical and computer laboratory exercises
  • Discussions Case Studies
COURSE BENEFITS

  • Improves the knowledge of quantitative models and methods which are important in economy and business.
  • Provides a practical and systematic approach to the modeling of business and economic data.
  • Turns the theory into practice through a number of interactive workshops and worked examples
  • Work on real-world problems related to up to date issues in the fields mentioned.
  • Employs sophisticated statistical packages.
  • Involves trainers who are experts in the subject matter.
  • Small class sizes meaning that individual attention is given.

QUANTITATIVE METHODS FOR BUSINESS AND ECONOMICS COURSE SYLLABUS
INTEGRATED BUSINESS FACULTY
Quantitative methods for business and economics Module

 

Lecturer: Marjan Nikolov, MSc Integrated Business Faculty
Teach. Ass. Aneta Vasiljevic-Shikaleska, Msc, Integrated Business Faculty
Course Objectives:

  • The course will enable students to learn how to use mathematical and statistical tools in the various areas of business and economics.
  • Course Description:
  • This module is designed as introductory text to provide students a strong knowledge in quantitative tools of applied economics and bussines through examples motivated by real data sets. It will enable students to analyze real-life economic and business problems.
  • Requirements
  • The course requires a thorough knowledge of mathematics at a gymnasium level.

Textbooks:

  1. J. Baldani, J. Bradfield, W. Turner, Mathematical economics, 2nd edition, 2005
  2. R. A. DeFusco, D. W. McLeavey, J. E. Pinto, D. E. Runkle, Quantitative methods for investment analysis, 2001R. J. Barro, X. Sala-i-Martin, Economic growth, 2001 (Appendix on mathematical methods)
  3. T. Sincich, Business statistics by example, V edition, Prentice Hall Inc, 1996
  4. P. Newbold, W.L. Carlson, B. Thorne, Statistics for business and econimics, VI Edition, Prentice Hall Inc., 2007
  5. D. F. Groebner, P.W. Shanon, P. C. Fry, K. D. Smith, Business statistics, a decision-making approach, Prentice Hall Inc., 2001
Course Syllabus
I. The time value of money
I.1. Interest rates and discount rates
I.2 Estimating cash flows for investment projects.
I.2.1 The future value of a single cash flow
I.2.2 The future value of a series of cash flows
I.2.3. The present value of a single cash flow
I.2.4. The present value of a series of cash flows
II. Economic functions
II.1.The production function.
II.2.Cost function.
II.3.The profit function
II.4.Break-even analysis.
III.Static Analysis
III.1. Equilibrium analysis in economics.
III.2. Linear models in business and economics.
III.3. Nonlinear models.
IV. Quantitative research principles
IV.1. Principles in collecting, summarizing and displaying business data.
IV.2. Graphical descriptions of qualitative and quantitative data
Case study: Warning: Cigarette smoke is hazardous to your health
V. Numerical methods for describing quantitative data
V.1. Measures of central tendency
V.2. Measures of variability
V.3. Measures of shape
Case study: Are chief executive officers (CEOs ) really worth their pay?
VI. Probability: Basic concepts
VI.1. Discrete probability distributions
VI.1.1. Binomial probability distribution
VI.1.2. Poisson probability distribution
Case study: Commitment to the firm: Stayers versus Leavers
VI.2. Continuous probability distribution
VI.2.1. The normal distribution and its business applications
Case study: Break-even analysis – when to market a new product
VII. Sampling and sampling distribution
VII.1. Sampling from a population
VII.2. The central limit theorem
VII.3. Acceptance Intervals
Case study: A decision problem for financial managers: When to investigate cost variances
VIII. Statistical inference: large samples
VIII.1. Estimation of parameters
VIII.2. Point and interval estimation of μ
VIII.3. Test of hypothesis
Case study: Public opinion polls: how accurate are they?
IX. Statistical inference: small samples
IX.1. Student’s distribution
IX.2.Test hypothesis and significance
IX.3.The Chi-square distribution
X Portfolio analysis
XI. Simple linear regression and correlation
XI.1. The method of least squares
XI.2. The coefficient of correlation
XI.3. The coefficient of determination
XI.4. Multiple regression
XII. Introduction to process and quality control
XII.1. Total quality management
XII.2. Variable control charts
XII.3. Control chart for means
XII. Control charts for standard deviations
Case study: Applying quality concepts to control the manufacture of steel rods.
XIII. Time series analysis and forecasting
XIII.1. Time series components
XIII.2. Index numbers
XIII.3.Smoothing methods
XIII.4.Forecasting using smoothing techniques
XIII.5.Forecasting using regression
Case study: Analyzing the price of your favorite stock