- Finished working with the CEO compensation and Wooldridge's "Beauty" datasets
- Explained Lesson 4.1 Discrete and semi-continuous regressors. Polynomial terms
- Started Lesson 4.2 Collinearity
- Solved the Exercise sheet #2
The goals for weeks 9-12 are:
- Finishing Lesson 4.2 Collinearity
- Doing a partial exam (final date: Wednesday April 10th) including all the course content up to and including discrete regressors
- Explaining Lessons 5.1 and 5.2, Heteroscedastic and non-normal dat and Influential observations and outliers, as well as the corresponding practical cases
I will not be able to attend to next April 11th class due to a professional meeting. We will compensate for the time lost with an extra class to answer doubts that will take place close to the June exam.
- Download the materials for lessons 5.1 and 5.2, as well as the corresponding practical cases
- Fit a log-linear regression to Wooldridge's "Beauty" dataset. Compare the results with those obtained with the linear model. Which model complies better with OLS hypotheses
Send an e-mail to this address (last day for delivery: Friday April 26th). This message should:
- Summarize the results of previous activities
- Describe any doubts about the topics explained in class
- Write a 400 words approx. summary of your main conclusions after fitting a log-linear regression to Wooldridge's "Beauty" dataset. Please, try to follow the guidelines in Givens, G.H. and J.A. Hoeting (2002). Comunicating Statistical Results.