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.
(113 reviews)
What you'll learn
Explain the three basic methods of Econometrics.
Apply different econometrics models to examples of daily life.
Interpret and carry out several basic analysis strategies (correlation, regression and distribution.
Ask relevant questions that can be analysed with basic tools.
Details to know
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There are 6 modules in this course
In this week you will be introduced to the MOOC Enjoyable Econometrics.
What's included
1 video1 discussion prompt
This week covers basic statistics like distributions, correlations and t-tests. You will be introduced to these concepts through real-life examples.
What's included
6 videos1 discussion prompt
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.
What's included
4 videos1 discussion prompt
This week covers the topic of multiple regression, which is introduced to you through examples from practice.
What's included
3 videos1 discussion prompt
In this week you will encounter different variants of multiple regression illustrated with examples.
What's included
3 videos
The last week of this MOOC focuses on real life cases that require more advanced econometric methods.
What's included
3 videos1 discussion prompt
Instructor
Offered by
Recommended if you're interested in Probability and Statistics
University of Virginia
Universiteit Leiden
University of Michigan
University of Michigan
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