Integration of Statistical Techniques in the Design Curriculum

Traditionally, design and analysis techniques have been using abstractions and models that are well captured using probabilistic models and are treated using standard algorithmic techniques. However, technology progress and application diversification, created a need for considering the impact of non-Gaussian and non-uniform uncertainty distributions that can only be addressed using non-parametric statistical techniques and robust algorithms. This trend provided an impetus for creation of a new graduate level course that aims to teach students sound statistical techniques, to enable them to obtain hands-on experience using statistical software, and to develop and apply the most effective ways to address design and manufacturing uncertainties. We summarize the syllabus of the course that integrates statistical techniques in the design curriculum, identifying the major obstacles and suggesting future improvements.