000			02017nam a22002177a 4500
003			OSt
005			20250131125635.0
008			250130b |||||||| |||| 00| 0 hin d
020			_a9781774698617
040			_aNISER LIBRARY _beng _cNISER LIBRARY
082			_a519.21 _bMOR-A
245			_aApplication of probability theory
260			_aCanada : _bArcler Press, _c2024
300			_axxiv, 375p.
504			_aIncludes Index.
520			_a"The Application of Probability Theory" is a comprehensive book that explores the diverse applications of probability theory across various fields, ranging from statistics and data analysis to machine learning and artificial intelligence, medical and health sciences, natural language processing, information retrieval, and engineering. The book delves into the fundamental principles and concepts of probability theory, such as sample space, events, probability distribution, random variables, probability laws, and expected value, and highlights the distinctions between frequentist and Bayesian approaches. With a collection of contemporaneous articles, it presents cutting-edge research and practical examples that showcase the relevance and impact of probability theory in understanding uncertainty, making predictions, assessing risks, designing experiments, and conducting statistical inference. Whether it's developing statistical models for missing data, enhancing machine learning algorithms with probability information, optimizing clinical trial designs for Alzheimer's disease, predicting urinary tract infections, or detecting fake news and hate speech, this book serves as a valuable resource for researchers, practitioners, and students seeking a deeper understanding of the applications of probability theory in today's rapidly evolving world.
650			_aProbability theory
700			_aMoreira, Olga _eed.
856			_3Reviews _uhttps://www.goodreads.com/book/show/199700010-the-application-of-probability-theory#CommunityReviews
942			_2udc _cBK
999			_c35563 _d35563