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返回到 测量社会科学中的因果效应

學生對 哥本哈根大学 提供的 测量社会科学中的因果效应 的評價和反饋

4.2
207 個評分
48 條評論

課程概述

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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AA
2021年1月10日

This is a challenging course, especially for those who only intend to breeze through the videos alone. Reading the recommended text before and/or after the videos is strongly advised.

M
2020年3月11日

Some Reading Materials such as journal articles on similar methods covered in course would have been a great inclusion as a part of the exercises.

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1 - 测量社会科学中的因果效应 的 25 個評論(共 48 個)

創建者 Lisa D

2017年3月9日

Unfortunately this course consists of the Professor reading his notes very quickly with rapid listing of concepts and very little time spent explaining complex topics. The quizzes emphasize the terms for various elements of the analysis rather than teaching how to work with the tools to analyze data. There does not seem to be anyone monitoring the course forum and mistakes in quiz questions and questions asked on the forum are not answered or replied to by anyone. I was committed to working with the course but by week 4 it was unfortunately impossible to absorb and there was no way to interact with anyone to get help. I'm sure there is room for improvement on this course and I hope the instructor does work to improve with the course, but currently the course is disappointing as a learning experience.

創建者 irene k

2017年6月30日

Lecturer extremely difficult to follow. Quiz questions required remembering numbers (!) from weeks earlier. In general a course based on good ideas, all missed in really bad execution of the course.

創建者 Tomasz J

2018年12月5日

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 Felipe C B

2018年2月20日

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.

創建者 Sophie W

2018年12月27日

The Professor has interpreted the course very detailed and thoroughly in terms of key methodologies and formulas. He also gave concrete examples and database to help me understand the theoretical knowledge. The quiz after each course are very helpful to understand new concepts and data implications in the examples. The only flaw might be too fast and not clear pronunciation of the instructor. Also, this is the only course about Impact Evaluation (i.e. RCT, IV, Diff-in-Diff) provided in Coursera. I hope there will be other similar courses available in Coursera!

創建者 Tiara A

2020年6月8日

Professor Holm provided a wealth of information in such a clear and succinct manner that learning the rigorous subject matter was not impossible. He provides the perfect balance of definitions and formulas along with interesting case studies. I highly recommend this course!

創建者 Aureliano A B

2018年5月16日

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 junseok k

2020年4月17日

I simply loved the lecture. I have considered to take other courses from Columbia University. But, it is much better for the beginner like me who have some statistical knowledge and no background in causal inference before. Thanking you very much.

創建者 Rohit V K

2018年12月13日

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 Andrej P

2020年3月29日

Causal effects in the Social sciences is a very difficult topic because experiments are often impossible in this field. This course provides some insightful techniques we can use to estimate a causal effect based on observed data.

創建者 Aedrian A

2021年1月11日

This is a challenging course, especially for those who only intend to breeze through the videos alone. Reading the recommended text before and/or after the videos is strongly advised.

創建者 Mohammad N A H

2020年3月12日

Some Reading Materials such as journal articles on similar methods covered in course would have been a great inclusion as a part of the exercises.

創建者 Aysha R

2019年9月11日

The course was well structured and helped to identify different approaches used to measure causality. Overall a well designed course.

創建者 niladri s b

2019年2月2日

This is a great course for people working in evaluating different social projects. Improved my insights a lot!

創建者 Eugenio D F

2017年1月8日

This is an useful course for medical researchs even though you can apply to other social science.

創建者 Olawoyin G A

2019年1月6日

I found it enlightening. It surely clarifies the concept of causality.

創建者 Jiacong L

2019年11月8日

Confusing concepts are presented clearly through examples. Thank you!

創建者 Sixtus A

2019年1月30日

Very useful course for people doing measurements in social sciences.

創建者 Николай Н

2019年7月16日

Отличный, специальный курс. Доступный но требует базовых знаний!

創建者 Vidya B R

2019年1月1日

Great material to review causal inference concepts.

創建者 Jie F

2019年2月13日

Very good short time course, highly recommended.

創建者 Lucas B

2018年10月30日

Very easy and intuitive

創建者 Monika B

2016年12月16日

Very good course!

創建者 Diego P

2017年3月2日

The course is great. Although it is really fast and requires some advanced understanding of algebra and statistics, it is not bad. However, I would reccommend to expand it and to include the advances in non-manipulative causation, as sustained by proff. J. Pearl and F. Squazzoni (specifically talking about sociology).

創建者 DR A N

2017年9月7日

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.