Report

Questions for Part 2. Data exploration

2.1 How are the variables related to each other? Comment on the strength of the dependence and report quantitative values. (1 point)

Questions for Part 3. Multivariate Gaussian distribution

3.1 How appropriate is the multivariate Gaussian distribution to model the joint distribution of the data? Comment both on the marginal distributions and the dependence between variables. You may want to use plots to illustrate your arguments. (2 points)

3.2 Assuming the safety thresholds \(S<30m/s\), \(D>45m\) and \(P<7s\), what is the probability of doing a passing maneuver under safe conditions? What is the difference between assuming independence or accounting for it using the multivariate Gaussian distribution? (1.75 points)

Questions for Part 4. Conditionalizing the multivariate Gaussian distribution

4.1 Given that you have observed a driver passing with D=53 m, what is the probability of that maneuver being safe? What is the difference between assuming independence and modeling dependence using the multivariate Gaussian distribution? (1.75 points)

4.2 How does the distribution change when conditionalizing in D = 53 m? You may want to report quantitative values of the parameters and use plots to support your arguments. (2.5 points)

By Patricia Mares Nasarre, Delft University of Technology. CC BY 4.0, more info on the Credits page of Workbook.