Convergence of Stochastic Processes
by D. Pollard
Publisher: Springer 1984
Number of pages: 223
An exposition od selected parts of empirical process theory, with related interesting facts about weak convergence, and applications to mathematical statistics. The high points of the book describe the combinatorial ideas needed to prove maximal inequalities for empirical processes indexed by classes of sets or classes of functions.
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by O. Melchert - arXiv
In these lecture notes, a selection of frequently required statistical tools will be introduced and illustrated. They allow to post-process data that stem from, e.g., large-scale numerical simulations (aka sequence of random experiments).
by Cappella Archive - Prasenjit Saha
This is a short book about the principles of data analysis. The emphasis is on why things are done rather than on exactly how to do them. If you already know something about the subject, then working through this book will deepen your understanding.
by Hossein Pishro-Nik - Kappa Research, LLC
This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, sciences, finance, and other fields. It provides a clear and intuitive approach to these topics.
by Brenda Meery - CK-12.org
CK-12 Foundation's Basic Probability and Statistics– A Short Course is an introduction to theoretical probability and data organization. Students learn about events, conditions, random variables, and graphs and tables that allow them to manage data.