About this Course

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Learner Career Outcomes

40%

started a new career after completing these courses

31%

got a tangible career benefit from this course

11%

got a pay increase or promotion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 30 hours to complete

Suggested: 7 weeks of study, 4-8 hours/week...

English

Subtitles: English

Skills you will gain

Linear RegressionTime SeriesEconometricsRegression Analysis

Learner Career Outcomes

40%

started a new career after completing these courses

31%

got a tangible career benefit from this course

11%

got a pay increase or promotion

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 30 hours to complete

Suggested: 7 weeks of study, 4-8 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1

Week 1

29 minutes to complete

Welcome Module

29 minutes to complete
2 videos (Total 9 min), 2 readings
2 videos
About this course5m
2 readings
Course Guide - Structure of the MOOC10m
Course Guide - Further information10m
8 hours to complete

Simple Regression

8 hours to complete
5 videos (Total 39 min), 11 readings, 1 quiz
5 videos
Lecture 1.2 on Simple Regression: Representation7m
Lecture 1.3 on Simple Regression: Estimation7m
Lecture 1.4 on Simple Regression: Evaluation8m
Lecture 1.5 on Simple Regression: Application6m
11 readings
Dataset Simple Regression10m
Training Exercise 1.11h
Solution Training Exercise 1.110m
Training Exercise 1.21h
Solution Training Exercise 1.210m
Training Exercise 1.31h
Solution Training Exercise 1.310m
Training Exercise 1.41h
Solution Training Exercise 1.410m
Training Exercise 1.51h
Solution Training Exercise 1.510m
Week
2

Week 2

9 hours to complete

Multiple Regression

9 hours to complete
6 videos (Total 45 min), 13 readings, 1 quiz
6 videos
Lecture 2.2 on Multiple Regression: Representation9m
Lecture 2.3 on Multiple Regression: Estimation8m
Lecture 2.4.1 on Multiple Regression: Evaluation - Statistical Properties8m
Lecture 2.4.2 on Multiple Regression: Evaluation - Statistical Tests5m
Lecture 2.5 on Multiple Regression: Application9m
13 readings
Dataset Multiple Regression10m
Training Exercise 2.11h
Solution Training Exercise 2.110m
Training Exercise 2.21h
Solution Training Exercise 2.210m
Training Exercise 2.31h
Solution Training Exercise 2.310m
Training Exercise 2.4.11h
Solution Training Exercise 2.4.110m
Training Exercise 2.4.21h
Solution Training Exercise 2.4.210m
Training Exercise 2.51h
Solution Training Exercise 2.510m
Week
3

Week 3

8 hours to complete

Model Specification

8 hours to complete
5 videos (Total 41 min), 11 readings, 1 quiz
5 videos
Lecture 3.2 on Model Specification: Specification9m
Lecture 3.3 on Model Specification: Transformation8m
Lecture 3.4 on Model Specification: Evaluation8m
Lecture 3.5 on Model Specification: Application9m
11 readings
Dataset Model Specification10m
Training Exercise 3.11h
Solution Training Exercise 3.110m
Training Exercise 3.21h
Solution Training Exercise 3.210m
Training Exercise 3.31h
Solution Training Exercise 3.310m
Training Exercise 3.41h
Solution Training Exercise 3.410m
Training Exercise 3.51h
Solution Training Exercise 3.510m
Week
4

Week 4

8 hours to complete

Endogeneity

8 hours to complete
5 videos (Total 44 min), 11 readings, 1 quiz
5 videos
Lecture 4.2 on Endogeneity: Consequences8m
Lecture 4.3 on Endogeneity: Estimation8m
Lecture 4.4 on Endogeneity: Testing7m
Lecture 4.5 on Endogeneity: Application9m
11 readings
Dataset Endogeneity10m
Training Exercise 4.11h
Solution Training Exercise 4.110m
Training Exercise 4.21h
Solution Training Exercise 4.210m
Training Exercise 4.31h
Solution Training Exercise 4.310m
Training Exercise 4.41h
Solution Training Exercise 4.410m
Training Exercise 4.51h
Solution Training Exercise 4.510m
4.6

167 Reviews

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Top reviews from Econometrics: Methods and Applications

By JJNov 16th 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.

By TMJun 9th 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.

Instructors

Image of instructor, Philip Hans Franses

Philip Hans Franses

Prof. Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Christiaan Heij

Christiaan Heij

Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Michel van der Wel

Michel van der Wel

Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Dennis Fok

Dennis Fok

Prof. Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Richard Paap

Richard Paap

Prof. Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Dick van Dijk

Dick van Dijk

Prof. Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Erik Kole

Erik Kole

Dr.
Econometric Institute, Erasmus School of Economics
Image of instructor, Francine Gresnigt

Francine Gresnigt

PhD candidate
Econometric Institute, Erasmus School of Economics
Image of instructor, Myrthe van Dieijen

Myrthe van Dieijen

PhD candidate
Econometric Institute, Erasmus School of Economics

About Erasmus University Rotterdam

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Frequently Asked Questions

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