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#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 31 hours to complete

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

#### English

Subtitles: English

### Skills you will gain

Linear RegressionTime SeriesEconometricsRegression Analysis

#### 100% online

Start instantly and learn at your own schedule.

#### Approx. 31 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
29 minutes to complete

## Welcome Module

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

## Simple Regression

5 videos (Total 39 min), 11 readings, 1 quiz
5 videos
Lecture 1.4 on Simple Regression: Evaluation8m
Lecture 1.5 on Simple Regression: Application6m
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
9 hours to complete

## Multiple Regression

6 videos (Total 45 min), 13 readings, 1 quiz
6 videos
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
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
8 hours to complete

## Model Specification

5 videos (Total 41 min), 11 readings, 1 quiz
5 videos
Lecture 3.4 on Model Specification: Evaluation8m
Lecture 3.5 on Model Specification: Application9m
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
8 hours to complete

## Endogeneity

5 videos (Total 44 min), 11 readings, 1 quiz
5 videos
Lecture 4.4 on Endogeneity: Testing7m
Lecture 4.5 on Endogeneity: Application9m
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
154 Reviews

## 44%

started a new career after completing these courses

## 36%

got a tangible career benefit from this course

## 12%

got a pay increase or promotion

### 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

### Philip Hans Franses

Prof. Dr.
Econometric Institute, Erasmus School of Economics

### Christiaan Heij

Dr.
Econometric Institute, Erasmus School of Economics

### Michel van der Wel

Dr.
Econometric Institute, Erasmus School of Economics

### Dennis Fok

Prof. Dr.
Econometric Institute, Erasmus School of Economics

### Richard Paap

Prof. Dr.
Econometric Institute, Erasmus School of Economics

### Dick van Dijk

Prof. Dr.
Econometric Institute, Erasmus School of Economics

### Erik Kole

Dr.
Econometric Institute, Erasmus School of Economics

### Francine Gresnigt

PhD candidate
Econometric Institute, Erasmus School of Economics

### Myrthe van Dieijen

PhD candidate
Econometric Institute, Erasmus School of Economics