The goal of this MOOC is to show that econometric methods are often needed to answer questions. A question comes first, then data are to be collected, and then finally the model or method comes in. Depending on the data, however, it can happen that methods need to be adapted. For example, where we first look at two variables, later we may need to look at three or more. Or, when data are missing, what then do we do? And, if the data are counts, like the number of newspaper articles citing someone, then matters may change too. But these modifications always come last, and are considered only when relevant.
An important motivation for me to make this MOOC is to emphasize that econometric models and methods can also be applied to more unconventional settings, which are typically settings where the practitioner has to collect his or her own data first. Such collection can be done by carefully combining existing databases, but also by holding surveys or running experiments. A byproduct of having to collect your own data is that this helps to choose amongst the potential methods and techniques that are around.
If you are searching for a MOOC on econometrics that treats (mathematical and statistical) methods of econometrics and their applications, you may be interested in the Coursera course “Econometrics: Methods and Applications” that is also from Erasmus University Rotterdam.
In this week you will be introduced to the MOOC Enjoyable Econometrics.
This week covers basic statistics like distributions, correlations and t-tests. You will be introduced to these concepts through real-life examples.
Simple regression is the focus of this week, real-life examples will help you to apply your knowledge. This week ends with a test to check if you've mastered the content of the first three weeks.
This week covers the topic of multiple regression, which is introduced to you through examples from practice.
Variants of multiple regression
In this week you will encounter different variants of multiple regression illustrated with examples.
New cases with new techniques
The last week of this MOOC focuses on real life cases that require more advanced econometric methods.
This audit-only/no-certificate free course, which I expected to be a casual introduction to econometrics principles for laypeople, is not as enjoyable as I thought it would be. This is especially in the latter half of the material, where barrages of increasingly...
This audit-only/no-certificate free course, which I expected to be a casual introduction to econometrics principles for laypeople, is not as enjoyable as I thought it would be. This is especially in the latter half of the material, where barrages of increasingly complicated equations are thrown at you at a quick pace. A way to get something from this course, particularly for non-economics or non-statistics majors like me, hopefully is slow down, pause and/or repeat the videos from time to time. The course assumes a lot that a student should have prior to entering the course such as knowledge of college-level mathematics and statistics. Nevertheless, the value of this course really lies in introducing the learners to the complexity of the field and the real-life necessity to understand such complexity. This course is highly recommended to prospective students of formal economics and/or econometrics courses or formal programs to help them gauge their baseline capacity to thrive in such offerings. I am looking forward to go back to the course materials from time to time should I take comprehensive courses on the field.