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Econometrics

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

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Rating 4.3 based on 129 ratings
Length 9 weeks
Effort 7 weeks of study, 4-8 hours/week
Starts Oct 12 (last week)
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
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

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.

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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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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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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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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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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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Rating 4.3 based on 129 ratings
Length 9 weeks
Effort 7 weeks of study, 4-8 hours/week
Starts Oct 12 (last week)
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
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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