Analysis and design of complex mechanical systems may involve uncertainty quantification knowing that in reality the dimensions, loads, properties, etc. are all random. The development of novel uncertainty quantification methods in conjunction with powerful numerical mechanics methods, namely stochastic isogeometric analysis is focused on with the application to the design and analysis of realistic mechanical systems. Mathematical tools are developed to quantify the randomness of an output of interest by bridging applied mathematics and mechanical engineering.