Discrete choice models are widely applied in areas such as transportation, energy, health, marketing, economics, environmental sciences, and more. Deep understanding of the underlying theoretical foundations and statistical methods is necessary to avoid making errors. By that we mean mistakes, not error terms or model disturbances. The course is designed for modelers who wish to acquire in-depth understanding and need “to get it right.” It is not intended for modelers seeking a “cookbook approach.” It combines mathematical presentation with intuitive interpretation, theory with hands-on real data practice, and behavioral reasoning with detailed statistical analysis.
This course has been successfully offered for more than 30 years, yet it is routinely updated to include the latest developments. It is a five-day course that begins with the basics of discrete choice and ends with advanced approaches to modeling, estimation, testing and stated preferences data collection.
One full-tuition scholarship will be awarded to an outstanding doctoral student. The deadline to apply for the full scholarship is May 1st. Partial (50%) tuition scholarships are also available for junior faculty, postdocs, and doctoral students.