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Measuring Causal Effects in the Social Sciences, University of Copenhagen

4.1
88 個評分
21 個審閱

課程信息

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....
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22 個審閱

創建者 Rohit Vishal Kumar

Dec 13, 2018

Good course with good explanation. But request please use a whiteboard instead of chalkboard in the background as the chalkboard becomes difficult to read on mobile devices. Some explanations can be augmented with additional reading

創建者 Tomasz Jankowski

Dec 05, 2018

This course makes clear distinction between different approaches to causality with nice graphics. That's good. But my feeling is that it uses explanation methods which are easy to understand only for those... who are already familiar with IV & DID. It's easy to find on the web more straight forward explanations on the web, yet still statistically rigorous.

While explanation level is always something very personal and can ba argued upon, there are clear flaws in the tests: 1) the way how questions are being asked suggest answer to the questions asked above. 2) questions are sometimes not precise enough, e.g. in module 5:

"What is the average test score for students who were in special education during 1st grade?"

should be

"What is the average test score for students AFTER KINDERGARTEN who were in special education during 1st grade?"

創建者 Lucas Braga

Oct 30, 2018

Very easy and intuitive

創建者 Tanay Mahindru

Oct 15, 2018

The course was enjoyable, though the transcripts to lectures were often incorrect. There was also no support on the forum for questions.

創建者 Xiaoxi Zhao

Jun 20, 2018

Some notations are not clearly defined.

創建者 Men Hoang

May 18, 2018

This is an very useful course for me who is studying Health Economics. However, the lack of interaction between lecturer and student makes this course more difficult.

創建者 Aureliano Angel Bressan

May 16, 2018

Great course! I finally understood the relation between RCT's, Instrumental Variables and DiDs. The prior suggested readings helped a lot, and the classes were very well conducted with intuitive explanations before the formal derivations that were also very helpful.

創建者 ryohasegawa

Apr 21, 2018

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

創建者 Tarjei Widding-Havneraas

Apr 06, 2018

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.

創建者 Felipe Orlando Gabriel Chávez Bustamante

Feb 21, 2018

On one hand, it is a very concise course that gives you some insights about the topic in question without unnecesary details of some basic topics. I really appreciated this, as many coursera courses take a lot of classes on explaining a lot of extremely basics contents where you take a lot of time . On the other hand, I took away two stars because the contents are poorely delivered by the instructor and if you do not have a grasp on the topic, is almost impossible to understand what is the lesson about. Questions are way too specific about details of the lectures (even specific numbers), and not about the general topic covered.