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Regular version of the site
Master 2022/2023

Data Analysis for Business Research

Type: Elective course (Master in International Business)
Area of studies: Management
When: 2 year, 1, 2 module
Mode of studies: offline
Open to: students of one campus
Instructors: Olga Makarova
Master’s programme: International Business
Language: English
ECTS credits: 6
Contact hours: 48

Course Syllabus

Abstract

The course aims at developing analytical skills for business research. During the course students will learn how to construct analytical system around the business that links strategy with perations. The application of modern business data analytical methods and tools to improve organizational performance will be studied iin practice. The students will learn about different types of data models, their relevance to particular business decisions and organising analytical system for managing divisional and segmental performance The course relies on data study, quantitative analysis and financial modelling which supports construction of explanatory and predictive models in the context of problem solving and organizational decision-making. Students will research and perform a real-case project how real business applies analytical tools in practice and construct and analyse analytical and financial models for business research.
Learning Objectives

Learning Objectives

  • This course equips students with basic analyticall frameworks and tools for strategic and operational decision-making in managing enterprise based on data analysis and data modelling
Expected Learning Outcomes

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.
  • Ability to analyse and decompose organization structural elements to create an analytical model for performance management
Course Contents

Course Contents

  • Introduction to data analysis
  • Basics of descriptive statistics
  • Principles of probability theory
  • Inferential statistics in business research
  • Statistical tests
Assessment Elements

Assessment Elements

  • non-blocking Test
  • non-blocking Examination assessment
Interim Assessment

Interim Assessment

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

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.

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.