Econometrics
Methods and Applications
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Rating | 4.4★ based on 167 ratings |
---|---|
Length | 9 weeks |
Effort | 7 weeks of study, 4-8 hours/week |
Starts | Jun 19 (45 weeks ago) |
Cost | $49 |
From | Erasmus University Rotterdam via Coursera |
Instructors | Myrthe van Dieijen, Philip Hans Franses, Dennis Fok, Erik Kole, Francine Gresnigt, Christiaan Heij, Dick van Dijk, Michel van der Wel, Richard Paap, Wendun Wang, Markus Mueller |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Math And Logic Probability And Statistics |
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What people are saying
hours a week
Studying all those videos, slides and exercise would take you many hours a week, but you will be very satisfying with modeling skills and working knowledge of time series learned from the course.
To finish the course I had to spend in excess of 20 hours a week to satisfactorily understand the material and be able to reproduce the main takeaways.
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learn a lot
I can learn a lot of basic conception about econometircs, and the training exercises is good for me to understand what the teachers has taught in the course!
It is a very good course I guess, but being 15 years old, it didn't make any sense.However, I got to learn a lot of new things about a field which I wish to pursue.
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understand the material
Good information, and detailed mathematical representation of the concepts, but often you will have to do outside research to truly understand the material, and the building blocks are not very helpful beyond a basic refresher course on matrices and statistics.
This class requires a lot of studying and initiative to seek outside help to understand the material.
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take this course
cool Excelente curso de econometria 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.
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! informative and inspiring if this is the first time taking econometrics, do not take this course.
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my opinion
The course is very good, but in my opinion too focused on theoretical demostrations above practical examples.
It is a good course, but a bit short in my opinion excellent course with a lot of practice This course was amazing!
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).
Some of the terminology doesn't seem congruent with what we use in North America The course it's great , however in my opinion it's too theoretical with few practical examples.If you're confortable with matrices and mathematics this course will provide you with very interesting tools and demostrations.I don't think that the course is for casual students, as it's very specific.
In my opinion, the course should be divided into two courses, especially extending the part of Time Series and with a much more practical approach with real cases and with prediction models.
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linear algebra
By studying this course I was hoping to learn about models and test them instead we are doing lousy math "as shown on the slide" and proving basic linear algebra properties... Not really what I was aiming for.
I found it difficult to follow the proofs and the heavy use of linear algebra scared me.
There's a strong requirement of linear algebra, calculus, and probability.
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well organized
It's both theoretical and practical, well organized!
Some stuff are treated briefly but overall is a good MOOC, well organized and gives good hints to deal with econometrics problems.
Excellent & Well organized course with great team!
They very detailed and well organized.
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rather than
The whole course seems as an outline , rather than a actual course by itself.
Old fashioned Econometrics course, still using the ideas of fixed regressors (rather than the more sensible conditional models approach), emphasizing prediction instead of causal interpretation, etc.
That approach really helped scaffold my learning.I hope you'd consider revisiting this course's learning plan - or probably just state on the course info page that this course is more suitable for a refresher course rather than an introductory one.
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statistical software
The only minor complaint that I have is that it still lacks some material on how to apply the methods using common programming languages or statistical software.
Maybe some blocks are too theoretical, there are some "bugs" in the content, and I miss a bit more of applied econometrics using statistical softwares.
It's worth trying if you are interested and comfortable with statistical software (Stata, SAS, R) or Excel with add-ins (eg RealStats).
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excelente curso
Excelente curso, muy bien ideado con muchos ejercicios para que queden bien grabados los conceptos, en un nivel no tan básico pero con toda la información necesaria para lograrlo.
Excelente curso para realizar análisis en mi trabajo e investigaciones.
really helpful
Assignments are also well made and really helpful.
It is really helpful!
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econometric theory
It is a well balanced course in combining econometric theory and its application.
The fact is that to apply econometric theory one needs to understand fair bit of econometric method (that includes matrix algebra, some properties of inner product space etc.)
Nice overview of econometric theory.
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Rating | 4.4★ based on 167 ratings |
---|---|
Length | 9 weeks |
Effort | 7 weeks of study, 4-8 hours/week |
Starts | Jun 19 (45 weeks ago) |
Cost | $49 |
From | Erasmus University Rotterdam via Coursera |
Instructors | Myrthe van Dieijen, Philip Hans Franses, Dennis Fok, Erik Kole, Francine Gresnigt, Christiaan Heij, Dick van Dijk, Michel van der Wel, Richard Paap, Wendun Wang, Markus Mueller |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Data Science Mathematics |
Tags | Data Science Math And Logic Probability And Statistics |
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