Topological and Statistical Methods for Complex Data : Tackling Large Scale High Dimensional and Multivariate Data Spaces I. Large scale data analysis: In situ and distributed analysis II. Large scale data analysis: Efficient representation of large functions III. Multi variate data analysis: Structural techniques IV. Multi variate data analysis: Classification and visualization of vector fields V. High dimensional data analysis: Exploration of high dimensional models VI. High dimensional data analysis: Analysis of large systems This book contains papers presented at the Workshop on the Analysis of Large scale High Dimensional and Multi Variate Data Using Topology and Statistics held in Le Barp France June 2013. It features the work of some of the most prominent and recognized leaders in the field who examine challenges as well as detail solutions to the analysis of extreme scale data. The book presents new methods that leverage the mutual strengths of both topological and statistical techniques to support the management analysis and visualization of complex data. It covers both theory and application and provides readers with an overview of important key concepts and the latest research trends. Coverage in the book includes multi variate and or high dimensional analysis techniques feature based statistical methods combinatorial algorithms scalable statistics algorithms scalar and vector field topology and multi scale representations. In addition the book details algorithms that are broadly applicable and can be used by application scientists to glean insight from a wide range of complex data sets