3rd Edition. — Chapman and Hall/CRC, 2019. — 487 p. — ISBN: 978-1138044487. Probability and Statistics for Computer Scientists, Third Edition helps students understand fundamental concepts of Probability and Statistics, general methods of stochastic modeling, simulation, queuing, and statistical data analysis; make optimal decisions under uncertainty; model and evaluate...
Path Ways To Clear Learning, 2012. — 551 p. — ISBN 9781493793457. Welcome… Fundamentals of Statistics & Probability Theory , a two volume textbook tutorial created by Howard Dachslager is an ideal tutorial resource for supporting both independent study and classroom textbook requirements. All major areas of elementary probability theory and statistics are covered in this...
Path Ways To Clear Learning, 2012. — 588 p. — ISBN 9781492245100. Welcome… Fundamentals of Statistics & Probability Theory , a two volume textbook tutorial created by Howard Dachslager is an ideal tutorial resource for supporting both independent study and classroom textbook requirements. All major areas of elementary probability theory and statistics are covered in this...
2nd Edition. — Springer Nature, 2024. — 180 p. — ISBN-13: 978-981-99-4661-7. This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs―Microsoft Excel, SPSS, and MatLAB. The book combining the...
9th Edition. — Pearson Education, 2024. — 1642 p. — ASIN: B0D7QFL855. For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant...
2nd, Revised and Extended Edition. — de Gruyter, 2024. — 370 p. — (De Gruyter Textbook). — ISBN 978-3-11-133232-1. The idea of the book is to present a text that is useful for both students of quantitative sciences and practitioners who work with univariate or multivariate probabilistic models. Since the text should also be suitable for self-study, excessive formalism is...
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