关于此课程： How can we know if the differences in wages between men and women are caused by discrimination or differences in background characteristics? In this PhD-level course we look at causal effects as opposed to spurious relationships. We will discuss how they can be identified in the social sciences using quantitative data, and describe how this can help us understand social mechanisms.
授课大纲
第 1 周
The Nature of Causal Effects and How to Measure Them
Welcome to the first week of the course! Thıs week we are looking at the nature of causal effects and how to measure them.
1 视频, 1 阅读材料
- Reading: Course information
- 视频: Lecture 1 - The Nature of Causal Effects and How to Measure Them
已评分: Module 1 Lecture Quiz
已评分: Module 1 Case Quiz
第 2 周
The Multivariate Regression Model and Mediating Factors
This second module introduces you multivariate regression model and the concept of mediating factors.
1 视频
已评分: Module 2 Lecture Quiz
已评分: Module 2 Case Quiz
第 3 周
Randomized Controlled Trials
In this third week of the course we are having a closer look at causality and the randomzied controlled trial.
第 4 周
Instrumental Variables
The fourth week of the course we will go through the concept of instrumental variables.
1 视频
已评分: Module 4 Lecture Quiz
已评分: Module 4a Case Quiz
已评分: Module 4b Case Quiz
第 5 周
Difference in Difference
The final module of the course deals with the difference in difference. We hope you enjoyed the course and have learned something that you can use in your future work and research.
常见问题解答
运作方式
Coursework
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制作方
哥本哈根大学
The University of Copenhagen is the oldest University in Denmark - founded in 1479, and with over 38,000 students and more than 9,000 employees. The purpose of the University is to conduct research and provide education to the highest academic level. Based in Denmark's capital city it is one of the top research institutions in Europe.
评分和审阅
Good course that takes participants from linear regression to RCT and approaches for causal inference in observational data. Four stars are given as some of the quizes include questions on specific estimates from lectures instead of more general aspects.
The course covers many important topics with good examples but could have been longer and more detailed about various assumptions and their violations. The accent of the instructor and many algebraic notations are diificult to understand for non-mathematicians or non-statisticians like myself.
Very good course! I learned a lot. I missed readings and other complementary material.
r
Throughout this course, I could deepen my understanding on practical use of statistics for social siceinces. Its simple mathematical proof on estimations methods is useful for practitioners