Research Methods (Analytical Thinking)

UNIVERSITÀ DELLA SVIZZERA ITALIANA
A Mendrisio (Svizzera)

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  • Corso
  • Mendrisio (Svizzera)
Descrizione

Descrizione This course aims at bringing students into a position in which they will not take every empirical or statistical result for granted. Thus, unlike the famous Bob Dylan-song, the general motto of this course is: “Do think twice, it’s not alright”! What does that mean? Oftentimes we are confronted with seemingly clear empirical facts that we interpret as obvious causal relations between two or (very rarely) more empirical factors. For example: an increase in revenues of a firm after the change of a CEO will usually be causally related to the CEO-change. The higher rejection rate for women who apply for admission at a university, on the other hand, will usually be interpreted as a discriminatory act of the university. But: is this really the case? Or do we have to look for different causes of these relations? Indeed, there exist many statistical pitfalls and fallacies that we usually tend to overlook, or are even unaware of, in everyday life. Very often these pitfalls exist because we do not take the influence of randomness into account. This course wants to uncover these pitfalls and fallacies and help future managers, not to get misled by seemingly obvious results. This course certainly does not possess direct applicability in practice. However, it fully aims at sharpening the analytical capabilities of students which should help them making better decisions in their professional life.

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Mendrisio
Tessin, Svizzera
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Programma

Descrizione

This course aims at bringing students into a position in which they will not take every empirical or statistical result for granted. Thus, unlike the famous Bob Dylan-song, the general motto of this course is: “Do think twice, it’s not alright”! What does that mean? Oftentimes we are confronted with seemingly clear empirical facts that we interpret as obvious causal relations between two or (very rarely) more empirical factors. For example: an increase in revenues of a firm after the change of a CEO will usually be causally related to the CEO-change. The higher rejection rate for women who apply for admission at a university, on the other hand, will usually be interpreted as a discriminatory act of the university. But: is this really the case? Or do we have to look for different causes of these relations? Indeed, there exist many statistical pitfalls and fallacies that we usually tend to overlook, or are even unaware of, in everyday life. Very often these pitfalls exist because we do not take the influence of randomness into account. This course wants to uncover these pitfalls and fallacies and help future managers, not to get misled by seemingly obvious results. This course certainly does not possess direct applicability in practice. However, it fully aims at sharpening the analytical capabilities of students which should help them making better decisions in their professional life.

In order to better explain the pitfalls and common misunderstandings of statistics, we will conduct several statistical experiments in which students have to, e.g., role dices or draw cards.