Objectives and competences
Students:
1. nhance their theoretical knowledge in the field of statistical methods.
2. Gain the ability to apply their theoretical knowledge in practice.
3. Acquire statistical approach to analysis of business problems and business decision making.
4. Acquire advanced knowledge of basic theoretical approaches in the field of business decision making using statistical methods.
Content (Syllabus outline)
Formulation of economic business problems in terms of statistics
Data collection methods – surveys and samples:
sampling and the quality of sampling data
survey design, sampling methods
Analysis of sample: weighting, standard error of estimation, sample variance, sampling frame, non-responses
Number of sampling units
Statistical techniques: estimation of parameters, hypothesis testing – two or more samples – independent and paired, related samples, ANOVA; association and dependencies
Preparation of the research report
Learning and teaching methods
lectures;
AV presentations;
case studies;
active individual and group work
Intended learning outcomes - knowledge and understanding
Development of knowledge and understanding:
Students:
1. Acquire specific knowledge in the field of mathematical and statistical methods for business problem solving.
2. Develop the skills to interpret the gained results by mathematical and statistical methods.
3. Learn how to analyse and synthesise different approaches in decision making.
4. Can demonstrate awareness of wider social and environmental ethical issues in the area of statistical data analysis.
Intended learning outcomes - transferable/key skills and other attributes
Cognitive/Intellectual skills:
Students:
1. Understand and apply critical analysis and theory development and their usability in solving real professional problems, with minimum guidance.
2. Synthesize different knowledge and procedures and are aware of importance of use of professional literature.
3. Can select appropriate techniques for problem solving and are able to evaluate the importance and significance of data.
4. Can identify key aspects of problem from different view points.
Key/Transferable skills
Students:
1. Further develop skills and expertise in the use of knowledge in a specific working area.
2. Upgrade the ability to become an autonomous learner.
3. Upgrade the ability to apply information technology.
4. Further develop their communication skills in an effective manner to effectively and professionally communicate.
Practical skills:
Students:
1. Are able to act autonomously with defined guidelines and certain level of supervision, in the field of statistical data analysis and interpretation of results.
Readings
Izbrana poglavja iz učbenikov:
Tominc, P. , Rožman, M. (2021). Statistična poslovna analiza, Univerza v Mariboru, Univerzitetna založba.
https://press.um.si/index.php/ump/catalog/book/572
Kalton, Vehovar (2001). Vzorčenje v anketah, FDV L.
McClave, J.T., Benson, P.G., Sincich, T. (2011). Statistics for Business and Economics, Pearson Prentice Hall,
Illowsky, B., Dean, S. (2012). Collaborative Statistics, Connexions, Accessed on May 10, 2019 at:
Open Textbook Library: https://open.umn.edu/opentextbooks/BookDetail.aspx?bookId=11
Additional information on implementation and assessment active participation in class discussions;
seminar research work;
written examination
The exam is passed when 28 out of 50 points are obtained by written axam AND at the same time, the sum together with points obtained by the active participation in class, equals at least 56 points (out of all 100).
20%
30%
50%
