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4.6

803 Bewertungen

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163 Bewertungen

Welcome!
Do you wish to know how to analyze and solve business and economic questions with data analysis tools? Then Econometrics by Erasmus University Rotterdam is the right course for you, as you learn how to translate data into models to make forecasts and to support decision making.
* What do I learn?
When you know econometrics, you are able to translate data into models to make forecasts and to support decision making in a wide variety of fields, ranging from macroeconomics to finance and marketing. Our course starts with introductory lectures on simple and multiple regression, followed by topics of special interest to deal with model specification, endogenous variables, binary choice data, and time series data. You learn these key topics in econometrics by watching the videos with in-video quizzes and by making post-video training exercises.
* Do I need prior knowledge?
The course is suitable for (advanced undergraduate) students in economics, finance, business, engineering, and data analysis, as well as for those who work in these fields. The course requires some basics of matrices, probability, and statistics, which are reviewed in the Building Blocks module. If you are searching for a MOOC on econometrics of a more introductory nature that needs less background in mathematics, you may be interested in the Coursera course “Enjoyable Econometrics” that is also from Erasmus University Rotterdam.
* What literature can I consult to support my studies?
You can follow the MOOC without studying additional sources. Further reading of the discussed topics (including the Building Blocks) is provided in the textbook that we wrote and on which the MOOC is based: Econometric Methods with Applications in Business and Economics, Oxford University Press. The connection between the MOOC modules and the book chapters is shown in the Course Guide – Further Information – How can I continue my studies.
* Will there be teaching assistants active to guide me through the course?
Staff and PhD students of our Econometric Institute will provide guidance in January and February of each year. In other periods, we provide only elementary guidance. We always advise you to connect with fellow learners of this course to discuss topics and exercises.
* How will I get a certificate?
To gain the certificate of this course, you are asked to make six Test Exercises (one per module) and a Case Project. Further, you perform peer-reviewing activities of the work of three of your fellow learners of this MOOC. You gain the certificate if you pass all seven assignments.
Have a nice journey into the world of Econometrics!
The Econometrics team...

Nov 16, 2015

The design of the course is very Helpful and efficient. The course is well explained. The instructors are very clear and master the subject. They very detailed and well organized.

Jun 09, 2016

Very practical, I would urge people who intend to take this course to come to this course with at least some knowledge of econometrics and statistics. It would come in handy.

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von LE T T T

•Jun 27, 2019

This course really laid a foundation on my research orientation. Sincerely thanks!

von Yuye D

•Jul 19, 2019

informative and inspiring

von Peiyao Z

•Aug 13, 2019

内容组织的很好，虽然课程不长，结合相关教材对计量经济学就可以有个基本扎实的基础了。老师的英语口音也很容易听懂！

von Madayan A

•Aug 24, 2019

Excellent courses, very good for practical application.

von sohaib

•Sep 01, 2019

Very Well Explain That man i am learning it in Pakistan

von gauri a

•Sep 02, 2019

As challenging as it can get! Definitely recommend for a rigorous training and understanding of econometrics

von Somanshu M

•Sep 06, 2019

One of the best courses.....

von Vianney B B E M

•Oct 28, 2019

concise effort has been deployed during the course to make econometrics accessecible, comprehensible by the simplicity of the lecture presentation, by the exercices training very closed to lectures. It'was so confortable to participate to this course.

von Bolívar E Á C

•Oct 27, 2019

Excelente curso para realizar análisis en mi trabajo e investigaciones.

von Swapan K P

•Nov 03, 2019

The course is well-designed with daily exercises for practice, and weekly tests (7) incl. Case Study in the last week. The course indeed helped me a lot to refresh theoretical knowledge that I learned nearly 2.5 decades ago during graduation/ master degree in Statistics. It's worth trying if you are interested and comfortable with statistical software (Stata, SAS, R) or Excel with add-ins (eg RealStats). Although I use Stata on a daily basis, I solved all problems in Excel Data Analysis and RealStats add-in in order to understand each steps clearly.

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von Aymen A

•Nov 03, 2019

perfect

von quangngu

•Jan 21, 2019

There was a drastic increase in difficulty in week 6 and 7 from the rest of the course.

von Thomas B

•Aug 25, 2018

Good content and quality. Coming from machine learning this gave me a new perspectives, e.g. a topic like endogeneity or the different kind of statistical tests.

I did the course using R, RStudio and R Markdown for the course assignments and that worked great. However, the course is taught without any reference to specific software packages and I think that's a big plus.

Some of the assignments were too academic for my taste (proving statements). I would have rather liked more examples showing different aspects and situations of the taught topics.

von James Z

•Feb 10, 2017

Lecture materials are very rich and well organized.

von Maximiliano G

•Sep 29, 2016

Un curso muy interesante, con mucho contenido que requiere un esfuerzo por parte de los alumnos y una base matemática/estadística sólida. Las prácticas están muy bien organizadas. Hay explicaciones que podrían mejorar. Sin embargo, cumple sobremanera mis expectativas. Lo recomiendo.

von ayushman g

•Dec 08, 2015

nicely explained.

von Taylor B

•May 08, 2016

This course is not for someone who hasn't taken much advanced math. There's a strong requirement of linear algebra, calculus, and probability. Someone who is relying only on the math prep they give you in the course will likely be very under-prepared for some of the more theoretical homework assignments.

With that disclaimer out of the way, this course gives a fairly good overview of important econometric techniques, though I wish they would have done more with time series analysis.

A major shortcoming of this course is some of the more complicated material (RESET test, Chow test, endogeneity, etc) were not presented in a complete way (in my opinion). I found myself referring to quite a few outside sources in order to figure out some of the more complicated material. Keep this in mind when taking the class and give yourself extra time to read farther into the concepts discussed in class.

von Utkarsh A

•Mar 18, 2017

The level of this course is high. It's better to take a basic course on Econometrics and then take up this.

von gao f

•Nov 24, 2016

many mistakes in the exercise solutions

von Arthur M

•Apr 10, 2016

Good content and exercise, very pedagogic.

The only problem are the use of the program: If you don't know how to use a statistical program such as R, you will spend more time struggling with the program than understanding the topic.

von Francesco

•Jul 23, 2017

Some stuff are treated briefly but overall is a good MOOC, well organized and gives good hints to deal with econometrics problems.

von Danish U

•Nov 05, 2015

Very good course. But too much emphasis on statistical derivations. Also estimating models by using any statistical software (SPSS, STATA, R, Eviews) will for sure be an interesting ad on.

von Софья

•Feb 22, 2017

Some topics that were covered in this course were not explained in details and, in addition, there was no explanation of the theoretical aspects of the course (for instance, formulas transcript ).

von Andrey P

•Jan 15, 2018

I'd be happy to have more practical excersises during the course instead/together with formula transformation tasks.

von Naim

•Aug 16, 2017

This course is really good for recapping what you have learned before. It would be a difficult course if you start it without previous background.

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