A Journey Into The Depths Of Probability And Statistics Inspiration Publishing
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The Fascination of Probability, Statistics and their Applications
Collecting together twenty-three self-contained articles, this volume presents the current research of a number of renowned scientists in both probability theory and statistics as well as their various applications in economics, finance, the physics of wind-blown sand, queueing systems, risk assessment, turbulence and other areas. The contributions are dedicated to and inspired by the research of Ole E. Barndorff-Nielsen who, since the early 1960s, has been and continues to be a very active and influential researcher working on a wide range of important problems. The topics covered include, but are not limited to, econometrics, exponential families, Lévy processes and infinitely divisible distributions, limit theory, mathematical finance, random matrices, risk assessment, statistical inference for stochastic processes, stochastic analysis and optimal control, time series, and turbulence. The book will be of interest to researchers and graduate students in probability, statistics and their applications.
High-Dimensional Statistics
Author: Martin J. Wainwright
language: en
Publisher: Cambridge University Press
Release Date: 2019-02-21
A coherent introductory text from a groundbreaking researcher, focusing on clarity and motivation to build intuition and understanding.
Probability and Statistics
Author: Dr. K. Karthikeyan, M.Sc.,M.Phil.,B.Ed.,Ph.D, Dr. Disha A. Shah, Dr. Kiran Singh Bais (Sisodiya), Dr. Jyoti Mishra
language: en
Publisher: QUILL TECH PUBLICATIONS
Release Date: 2025-07-04
Probability and Statistics is a structured and student-friendly textbook that provides a deep exploration of fundamental and advanced concepts in probability theory and statistical analysis. Designed to serve a broad audience, including undergraduate and postgraduate students across mathematics, engineering, computer science, and applied sciences, this book offers both clarity and rigor in its approach. The content spans a wide range of topics beginning with foundational definitions of probability—classical, statistical, and axiomatic—and progresses into the study of random variables, moment-generating functions, and core probability theorems. It thoroughly explores discrete and continuous probability distributions, such as Binomial, Poisson, and Normal, making it ideal for both theoretical understanding and practical application. Further sections delve into descriptive statistics, measures of central tendency and dispersion, correlation, regression, and multivariate analysis. A dedicated chapter on hypothesis testing equips readers with essential tools for making inferences from data, covering t-tests, chi-square tests, F-tests, and large-sample methods. The final part of the book introduces the principles of experimental design, with emphasis on analysis of variance (ANOVA) and factorial experiments—key techniques in statistical research and industrial studies. Packed with illustrative examples, solved problems, and exercise sets, the book supports self-learning while encouraging analytical thinking. It is especially useful for those preparing for academic exams, research work, and data-driven decision-making in professional environments. This textbook bridges theoretical insights with real-world applications, making it a valuable resource for both classroom learning and independent study.