Semester: 4
ECTS: 5
Lectures: 30
Practice sessions: 30
Independent work: 90
Module Code: 24-321-0163
Semester: 4
ECTS: 5
Lectures: 30
Practice sessions: 30
Independent work: 90
Module Code: 24-321-0163
Module title:
Quantitative methods and modelling
Lecturers and associates:
Module overview:
This module introduces students the basic statistical concepts, methods and ways of thinking required to solve statistical problems. The main goals of the module are:
Introduce students with appropriate methods of descriptive statistics and its practical usage (bivariate and univariate).
Introduce linear regression as a basic machine learning algorithm.
Usage appropriate methods of parameter estimation and statistical tests and results interpretation.
Research hypotheses formulation, evaluate them using statistical methods, and summarize the results in a research paper.
The module does require some basic statistical and mathematical knowledge. It will enable students to independently apply quantitative analysis and through examples and exercises develop the knowledge, understanding and skills of modelling realistic problems.
In this module students will learn:
Choose and apply appropriate methods of descriptive statistics and interpret results (univariate and bivariate).
Calculate and interpret best – fit line for linear regression.
Choose and apply appropriate methods of parameter estimation and statistical tests and interpret results.
Formulate research hypotheses, evaluate them using statistical methods, and summarize the results in a research paper.
Literature:
Required readings:
Albright, S. Ch., Winston, W. (2015). Business Analytics: Data Analysis and Decision Making, 5th Edition. Andover: CENGAGE Learning.