Statistical Modeling And Analysis For Complex Data Problems

This book reviews some of today’s more complex problems, and reflects some of the important research directions in the field. Twenty-nine authors – largely from Montreal’s GERAD Multi-University Research Center and who work in areas of theoretical statistics, applied statistics, probability theory, and stochastic processes – present survey chapters on various theoretical and applied problems of importance and interest to researchers and students across a number of academic domains.

This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills—Data Analysis, Business Modeling, and Simulation of Complex Problems.

This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills—Data Analysis, Business Modeling, and Simulation of Complex Problems.

The modeling and processing of empirical data is one of the main subjects and goals of statistics. Nowadays, with the development of computer science, the extraction of useful and often hidden information and patterns from data sets of different volumes and complex data sets in warehouses has been added to these goals. New and powerful statistical techniques with machine learning (ML) and data mining paradigms have been developed.