Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap
in engineering and science education and practice for both students and practitioners. It
demonstrates how to apply concepts and methods learned in disparate courses such as
mathematical modeling probability statistics experimental design regression model building
optimization risk analysis and decision-making to actual engineering processes and systems.
The text provides a formal structure that offers a basic broad and unified perspective while
imparting the knowledge skills and confidence to work in data analysis and modeling. This
volume uses numerous solved examples published case studies from the author¿s own research
and well-conceived problems in order to enhance comprehension levels among readers and their
understanding of the ¿processes¿along with the tools.
