Introduction To Probability And Statistics For Engineers And Scientists

Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0123948428
Size: 40.22 MB
Format: PDF, Docs
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Introduction to Probability and Statistics for Engineers and Scientists provides a superior introduction to applied probability and statistics for engineering or science majors. Ross emphasizes the manner in which probability yields insight into statistical problems; ultimately resulting in an intuitive understanding of the statistical procedures most often used by practicing engineers and scientists. Real data sets are incorporated in a wide variety of exercises and examples throughout the book, and this emphasis on data motivates the probability coverage. As with the previous editions, Ross' text has tremendously clear exposition, plus real-data examples and exercises throughout the text. Numerous exercises, examples, and applications connect probability theory to everyday statistical problems and situations. Clear exposition by a renowned expert author Real data examples that use significant real data from actual studies across life science, engineering, computing and business End of Chapter review material that emphasizes key ideas as well as the risks associated with practical application of the material 25% New Updated problem sets and applications, that demonstrate updated applications to engineering as well as biological, physical and computer science New additions to proofs in the estimation section New coverage of Pareto and lognormal distributions, prediction intervals, use of dummy variables in multiple regression models, and testing equality of multiple population distributions.

Probability And Statistics For Engineers And Scientists

Author: Anthony J. Hayter
Publisher: Cengage Learning
ISBN: 1133712762
Size: 49.20 MB
Format: PDF, Docs
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PROBABILITY AND STATISTICS FOR ENGINEERS AND SCIENTISTS, Fourth Edition, continues the student-oriented approach that has made previous editions successful. As a teacher and researcher at a premier engineering school, author Tony Hayter is in touch with engineers daily--and understands their vocabulary. The result of this familiarity with the professional community is a clear and readable writing style that students understand and appreciate, as well as high-interest, relevant examples and data sets that keep students' attention. A flexible approach to the use of computer tools, including tips for using various software packages, allows instructors to choose the program that best suits their needs. At the same time, substantial computer output (using MINITAB and other programs) gives students the necessary practice in interpreting output. Extensive use of examples and data sets illustrates the importance of statistical data collection and analysis for students in the fields of aerospace, biochemical, civil, electrical, environmental, industrial, mechanical, and textile engineering, as well as for students in physics, chemistry, computing, biology, management, and mathematics. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Introduction To Probability And Statistics For Scientists And Engineers

Author: Walter A. Rosenkrantz
Publisher: McGraw-Hill Science, Engineering & Mathematics
ISBN: 9780070539884
Size: 56.50 MB
Format: PDF, ePub
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This modern text presents the fundamental ideas of probability theory and statistics with an abundance of applications relating to topics such as reliability, queuing theory, and computer performance analysis. Along with thorough coverage of the traditional topics of a first course in statistics, this new text emphasizes modeling, displaying, interpreting, and collecting data for a variety of scientific and engineering applications.

Introduction To Probability And Statistics For Science Engineering And Finance

Author: Walter A. Rosenkrantz
Publisher: CRC Press
ISBN: 9781584888130
Size: 57.24 MB
Format: PDF, ePub, Mobi
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Integrating interesting and widely used concepts of financial engineering into traditional statistics courses, Introduction to Probability and Statistics for Science, Engineering, and Finance illustrates the role and scope of statistics and probability in various fields. The text first introduces the basics needed to understand and create tables and graphs produced by standard statistical software packages, such as Minitab, SAS, and JMP. It then takes students through the traditional topics of a first course in statistics. Novel features include: Applications of standard statistical concepts and methods to the analysis and interpretation of financial data, such as risks and returns Cox–Ross–Rubinstein (CRR) model, also called the binomial lattice model, of stock price fluctuations An application of the central limit theorem to the CRR model that yields the lognormal distribution for stock prices and the famous Black–Scholes option pricing formula An introduction to modern portfolio theory Mean-standard deviation diagram of a collection of portfolios Computing a stock’s betavia simple linear regression As soon as he develops the statistical concepts, the author presents applications to engineering, such as queuing theory, reliability theory, and acceptance sampling; computer science; public health; and finance. Using both statistical software packages and scientific calculators, he reinforces fundamental concepts with numerous examples.

Introduction To Probability And Statistics For Engineers

Author: Milan Holický
Publisher: Springer Science & Business Media
ISBN: 3642383009
Size: 33.98 MB
Format: PDF, Kindle
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The theory of probability and mathematical statistics is becoming an indispensable discipline in many branches of science and engineering. This is caused by increasing significance of various uncertainties affecting performance of complex technological systems. Fundamental concepts and procedures used in analysis of these systems are often based on the theory of probability and mathematical statistics. The book sets out fundamental principles of the probability theory, supplemented by theoretical models of random variables, evaluation of experimental data, sampling theory, distribution updating and tests of statistical hypotheses. Basic concepts of Bayesian approach to probability and two-dimensional random variables, are also covered. Examples of reliability analysis and risk assessment of technological systems are used throughout the book to illustrate basic theoretical concepts and their applications. The primary audience for the book includes undergraduate and graduate students of science and engineering, scientific workers and engineers and specialists in the field of reliability analysis and risk assessment. Except basic knowledge of undergraduate mathematics no special prerequisite is required.

Probability And Statistics For Engineering And The Sciences

Author: Jay L. Devore
Publisher: Cengage Learning
ISBN: 1305465326
Size: 26.70 MB
Format: PDF, ePub
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Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th Edition. Always a favorite with statistics students, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals apply concepts, models, and methodologies in today's engineering and scientific careers. Jay Devore, an award-winning professor and internationally recognized author and statistician, emphasizes authentic problem scenarios in a multitude of examples and exercises, many of which involve real data, to show how statistics makes sense of the world. Mathematical development and derivations are kept to a minimum. The book also includes output, graphics, and screen shots from various statistical software packages to give you a solid perspective of statistics in action. A Student Solutions Manual, which includes worked-out solutions to almost all the odd-numbered exercises in the book, is available. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Probability And Statistics For Engineers And Scientists

Author: Anthony J. Hayter
Publisher: Duxbury Press
ISBN:
Size: 23.33 MB
Format: PDF
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This introduction to probability and statistics for engineering and science students focuses on the fundamental concepts of statistical analysis, not on mathematical details or obscure techniques. The sequence of topics will fit almost all one-semester applied probability and statistics courses. The clear, thorough presentation of basic concepts is balanced by a wealth of applied examples and problems. Numerous in-text examples, problems, and real-life applications and illustrations demonstrate how a variety of computer-based statistical software packages (including Minitab) may be used in statistical analysis.

Probability And Statistics For Computer Scientists Second Edition

Author: Michael Baron
Publisher: CRC Press
ISBN: 1439875901
Size: 10.56 MB
Format: PDF, Kindle
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Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic modeling, simulation, and data analysis; make optimal decisions under uncertainty; model and evaluate computer systems and networks; and prepare for advanced probability-based courses. Written in a lively style with simple language, this classroom-tested book can now be used in both one- and two-semester courses. New to the Second Edition Axiomatic introduction of probability Expanded coverage of statistical inference, including standard errors of estimates and their estimation, inference about variances, chi-square tests for independence and goodness of fit, nonparametric statistics, and bootstrap More exercises at the end of each chapter Additional MATLAB® codes, particularly new commands of the Statistics Toolbox In-Depth yet Accessible Treatment of Computer Science-Related Topics Starting with the fundamentals of probability, the text takes students through topics heavily featured in modern computer science, computer engineering, software engineering, and associated fields, such as computer simulations, Monte Carlo methods, stochastic processes, Markov chains, queuing theory, statistical inference, and regression. It also meets the requirements of the Accreditation Board for Engineering and Technology (ABET). Encourages Practical Implementation of Skills Using simple MATLAB commands (easily translatable to other computer languages), the book provides short programs for implementing the methods of probability and statistics as well as for visualizing randomness, the behavior of random variables and stochastic processes, convergence results, and Monte Carlo simulations. Preliminary knowledge of MATLAB is not required. Along with numerous computer science applications and worked examples, the text presents interesting facts and paradoxical statements. Each chapter concludes with a short summary and many exercises.