For junior/senior undergraduates taking a one-semester probability and statistics course as applied to engineering, science, or computer science. This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in the fields of engineering and the sciences. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. Students using this text should have the equivalent of the completion of one semester of differential and integral calculus.
essentials of probability statistics for engineers scientists pearson new international edition
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Normal 0 false false false This text covers the essential topics needed for a fundamental understanding of basic statistics and its applications in the fields of engineering and the sciences. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. The authors assume one semester of differential and integral calculus as a prerequisite.
A valuable resource for students and teachers alike, this second edition contains more than 200 worked examples and exam questions.
Provides statistical modeling and simulating approaches to address the needs for intrusion detection and protection. Covers topics such as network traffic data, anomaly intrusion detection, and prediction events.
This subject is critical in many modern applications such as mathematical finance, quantitative management, telecommunications, signal processing, bioinformatics, as well as traditional ones such as insurance, social science and engineering. The authors have rectified deficiencies in traditional lecture-based methods by collecting together a wealth of exercises for which they have supplied complete solutions. These solutions are adapted to needs and skills of students. Experience shows that users of this book will find the subject more interesting and they will be better equipped to solve problems in practice and under examination conditions.
The revision of this well-respected text presents a balanced approach of the classical and Bayesian methods and now includes a chapter on simulation (including Markov chain Monte Carlo and the Bootstrap), coverage of residual analysis in linear models, and many examples using real data. Probability & Statistics, Fourth Edition, was written for a one- or two-semester probability and statistics course. This course is offered primarily at four-year institutions and taken mostly by sophomore and junior level students majoring in mathematics or statistics. Calculus is a prerequisite, and a familiarity with the concepts and elementary properties of vectors and matrices is a plus.
Previously published: Basic business statistics: concepts and applications / Mark L. Berenson, David M. Levine, Timothy C. Krehbiel. Boston: Prentice Hall, c2012.