Data Analysis for Business Research

2022/2023

Academic Year

ENG

Instruction in English

6

ECTS credits

Delivered at:

Department of Management

Course type:

Elective course

When:

2 year, 1, 2 module

Instructor

Makarova, Olga

Course Syllabus

Abstract

The course aims at developing analytical skills for business research. The students will learn about different types of data, their relevance to particular markets and customer behaviour. The course relies on statistical and quantitative analysis and helps students to build explanatory and predictive models in the context of problem solving and organizational decision making.

Learning Objectives

• This course equips students with basic statistical frameworks.

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

Assessment Elements

• Test
• Examination assessment

Interim Assessment

• 2022/2023 2nd module
  0.6 * Examination assessment + 0.2 * Test

Bibliography

Recommended Core 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.
• 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

• 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.