Introduction to Probability and Statistics for Engineers and Scientists

Author: Sheldon M. Ross
Publisher: Academic Press
ISBN: 0123948428
Format: PDF, Mobi
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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.

Introduction to Probability and Statistics for Engineers

Author: Milan Holický
Publisher: Springer Science & Business Media
ISBN: 3642383009
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 Engineers and Scientists

Author: Anthony J. Hayter
Publisher: Duxbury Press
ISBN:
Format: PDF, Docs
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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.

Statistics and Probability with Applications for Engineers and Scientists

Author: Bhisham C. Gupta
Publisher: John Wiley & Sons
ISBN: 1118522206
Format: PDF, ePub, Mobi
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Introducing the tools of statistics and probability from the ground up An understanding of statistical tools is essential for engineers and scientists who often need to deal with data analysis over the course of their work. Statistics and Probability with Applications for Engineers and Scientists walks readers through a wide range of popular statistical techniques, explaining step-by-step how to generate, analyze, and interpret data for diverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probability with Applications for Engineers and Scientists covers descriptive statistics first, then goes on to discuss the fundamentals of probability theory. Along with case studies, examples, and real-world data sets, the book incorporates clear instructions on how to use the statistical packages Minitab® and Microsoft® Office Excel® to analyze various data sets. The book also features: • Detailed discussions on sampling distributions, statistical estimation of population parameters, hypothesis testing, reliability theory, statistical quality control including Phase I and Phase II control charts, and process capability indices • A clear presentation of nonparametric methods and simple and multiple linear regression methods, as well as a brief discussion on logistic regression method • Comprehensive guidance on the design of experiments, including randomized block designs, one- and two-way layout designs, Latin square designs, random effects and mixed effects models, factorial and fractional factorial designs, and response surface methodology • A companion website containing data sets for Minitab and Microsoft Office Excel, as well as JMP ® routines and results Assuming no background in probability and statistics, Statistics and Probability with Applications for Engineers and Scientists features a unique, yet tried-and-true, approach that is ideal for all undergraduate students as well as statistical practitioners who analyze and illustrate real-world data in engineering and the natural sciences.

Introduction to Probability and Statistics for Scientists and Engineers

Author: Walter A. Rosenkrantz
Publisher: McGraw-Hill Science, Engineering & Mathematics
ISBN: 9780070539884
Format: PDF, Kindle
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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.

Probability and Statistics for Engineering and the Sciences

Author: Jay L. Devore
Publisher: Cengage Learning
ISBN: 1305465326
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 Statistics for Engineers Scientists MyStatLab Global Edition

Author: Ronald E. Walpole
Publisher: Pearson Higher Ed
ISBN: 1292161418
Format: PDF, Docs
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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 applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding. This latest edition is also available in as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book. MyStatLab™ is not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MyStatLab is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts.

Fundamentals of Probability and Statistics for Engineers

Author: T. T. Soong
Publisher: John Wiley & Sons
ISBN: 0470868155
Format: PDF
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This textbook differs from others in the field in that it has been prepared very much with students and their needs in mind, having been classroom tested over many years. It is a true “learner’s book” made for students who require a deeper understanding of probability and statistics. It presents the fundamentals of the subject along with concepts of probabilistic modelling, and the process of model selection, verification and analysis. Furthermore, the inclusion of more than 100 examples and 200 exercises (carefully selected from a wide range of topics), along with a solutions manual for instructors, means that this text is of real value to students and lecturers across a range of engineering disciplines. Key features: Presents the fundamentals in probability and statistics along with relevant applications. Explains the concept of probabilistic modelling and the process of model selection, verification and analysis. Definitions and theorems are carefully stated and topics rigorously treated. Includes a chapter on regression analysis. Covers design of experiments. Demonstrates practical problem solving throughout the book with numerous examples and exercises purposely selected from a variety of engineering fields. Includes an accompanying online Solutions Manual for instructors containing complete step-by-step solutions to all problems.