Upon completion of this course, students should be able to:

1) Define and explain the following concepts: Conjoint analysis 
(full profile, self-explicated, hybrid methods (including 
adaptive conjoint analysis (ACA)), discrete choice analysis, 
experimental design for conjoint and discrete choice, latent 
class methods, hierarchical bayes methods.

2) Perform conjoint and discrete choice analysis for real 
marketing research applications.  Tasks would include: 
formulation of the problem, questionnaire construction, creation 
of the appropriate design, model estimation and analysis, 
validation, reporting results and prediction. 

3) Evaluate, interpret, and utilize conjoint and discrete choice 
studies performed by others.

4) Recall recent advances in conjoint and discrete choice that 
appear in the practitioner oriented literature.

Conjoint Analysis Fundamentals and Self-Explicated Methods
Reporting Conjoint Results: Descriptives and Conjoint Simulators
Experimental Design for Conjoint
Conjoint Modeling and Estimation
Conjoint Applications
Discrete Choice Fundamentals
Experimental Design for Discrete Choice Analysis
Discrete Choice Modeling and Estimation
Reporting Discrete Choice Results: Descriptives and Discrete 
   Choice Simulators
Discrete Choice Applications
Latent Class Methods
Hierarchical Bayes Methods