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Analytical Thinking

Description

Course objectives

This course will encourage students not take empirical or statistical claims for granted and it will equip them with the skills to critically evaluate these claims. This will be accomplished (almost completely) without mathematics – just with analytical and logical thinking.

 

Contents

Often, we are confronted with seemingly clear empirical facts that we interpret as obvious causal relations between two or more empirical factors. For example, an increase in revenues of a firm after the change of the CEO will usually be causally related to the CEO-change. Is this really the case? Or do we have to look for different causes of these relations?

There exist many statistical pitfalls and fallacies that we tend to overlook, or are even unaware of, in everyday life. This course introduces students to these pitfalls and enables them to read statistical arguments critically. Covering key areas of where statistical claims can ‘go wrong’ – that is, where false conclusions tend to be drawn from seemingly self-evident data – the course sharpens students’ analytical capabilities, allowing them to make better decisions in their professional career.

 

Structure
The course consists of seminars. It is a practice-based course, where students participate in experiments or solve in-class exercises either individually or in small groups.

Grading
The grade is based on the final assignment. The final assignment is an exam on the topics discussed in class.

 
Textbooks and/or bibliography
Selected chapters of
Campbell, S. K. (2012). Flaws and fallacies in statistical thinking. Englewood Cliffs: Prentice-Hall
Clark, M. (2007). Paradoxes from A to Z. 2nd ed. London: Routledge

People

 

Beck N.

Course director

Additional information

Semester
Fall
Academic year
2019-2020
ECTS
3
Language
English
Education
Master of Science in Economics in Economic Policy (until A.Y. 2018), Elective course, Elective course, 2nd year

Master of Science in Economics in Management, Elective course, Track in Organization and Human Resources Management, 2nd year

Master of Science in Management and Informatics, Elective course, Lecture, 2nd year