2022/2023
Data Analysis for Business Research
Type:
Mago-Lego
Delivered by:
Department of Management
When:
1, 2 module
Open to:
students of one campus
Instructors:
Olga Makarova
Language:
English
ECTS credits:
6
Contact hours:
48
Course Syllabus
Abstract
The course covers aspects of business-planning in an enterprise and performance management in financial perspective. Starting with foundamental strategic and architecrural concepts and questions on linking strategy with operations, students then deep dive into profitability and cost analysis accompanied with revenue planning, will study business modelling, planning and budgeting instruments that support decision-making process in an organization. Students will work with financial models and will analyse in practice strategy-operations linkage and operational financial performance management
Learning Objectives
- This course equips students with basic analytical! frameworks and tools for strategic and operational decision-making in managing enterprise based on financial data analysis and data modelling
Expected Learning Outcomes
- Able to choose statistical methods appropriate to their data and substantive research problem
- Able to conduct descriptive statistics on quantitative data, apply basic statistical methods and interpret results of analysis
- Application of basic tools (plots, graphs, summary statistics) to carry out exploratory data analysis.
Course Contents
- Introduction to data analysis
- Basics of descriptive statistics
- Principles of probability theory
- Inferential statistics in business research
- Statistical tests
Bibliography
Recommended Core Bibliography
- Rohatgi, V. K., & Saleh, A. K. M. E. (2015). An Introduction to Probability and Statistics (Vol. 3rd edition). Hoboken, New Jersey: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1050364
Recommended Additional Bibliography
- Fraser C. Business statistics for competitive advantage with Excel 2016: basics, model building, simulation and cases. New York, NY: Springer Science+Business Media, 2016. 475 с.
- Groebner, David, et al. Business Statistics, EBook, Global Edition, Pearson Education, Limited, 2018. ProQuest Ebook Central, https://ebookcentral.proquest.com/lib/hselibrary-ebooks/detail.action?docID=5186156.
- Rasch, D., Verdooren, L. R., & Pilz, J. (2019). Applied Statistics : Theory and Problem Solutions with R. Hoboken, NJ: Wiley. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=2218318
- Zelterman, D. (2015). Applied Multivariate Statistics with R. Springer.