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First some definitions regarding econometrics, regressions, types of data and independent and dependent variables are given. Then the basic function of a simple regression analysis is explained. Lastly, there is discussion of the meaning of the error term.
Econometrics // Lecture 1: Introduction
Sporting events can be seen as controlled, real-world, miniature laboratory environments, approaching the idea of “holding other things equal” when exploring the implications of decisions, incentives, and constraints in a competitive setting (Goff and Tollison 1990, Torgler 2009). Thus, a growing number of studies have used sports data to study decision-making questions that have guided behavioral economics literature.
Sport as a Behavioral Economics Lab
This course will expose students to some of the key debates that link digital transformations to economic, social, and political inequalities. Students will be familiarised with a variety of theoretical movements in development studies and internet studies: exploring thinking that frames the internet as a leveller that can bridge divides vs. exploring the internet as an infrastructure that amplifies existing inequalities.
Digital Capitalism and its Inequalities
This course introduces the main topics in Econometrics by using R statistical software. The relation of themes is comprehensive and includes the basic notions such as linear regression, multiple regression, causal inference, regression discontinuity and instrumental variable. In total, the course covers thirteen chapters that are common in any undergraduate econometrics course.
Introduction to Econometrics with R
Regression Analysis: A Constructive Critique identifies a wide variety of problems with regression analysis as it is commonly used and then provides a number of ways in which practice could be improved.
Regression Analysis
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