Statistics for managerial decision making 2637-EMBA-EN-SMDM
The aim of the course is to prepare students for an effective use of statistical and data mining methods in the manager's work. Using quantitative data analysis requires critical scrutiny of the results of various measurements, evaluation of various types of data, and validation of conclusions reached. Understanding the fundamentals of data analysis, and key steps of the process, significantly increases the chances of successful use of quantitative data to support decision making, avoiding methodological and ethical traps in the process.
Type of course
Mode
Course coordinators
Learning outcomes
Knowledge and skills:
• distinguish main categories of data analysis tasks in business (e.g. classification, “value estimation” via regression analysis, similarity matching, co-occurrence grouping etc.)
• distinguish correlation from causation
• deal with missing data
• match an appropriate method of analysis with a research problem and measurement type
• understand basic concepts behind ‘big data’ and machine learning
• understand rules of creating good questionnaire items and common mistakes made in the process
• structure management problems so that they can be expressed in terms of quantitative data and analysed using methods of statistics and data science
• create predictive models
Cognitive competences:
• understand the role of empirical research and research methodology
• develop habits of critical analysis and sceptical approach to presented explanations and conclusions
• develop tendency to look for alternative interpretations for quantitative research results
• understand methodological and ethical pitfalls of faulty research procedures and improper generalisation of conclusions
Assessment criteria
• Individual and group in-class activities – a total of 40%
• Exercises on the e-learning platform – 30%
• Final project (in teams) - 30%
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: