**Author**: Jay L. Devore

**Publisher:**Cengage Learning

**ISBN:**1305465326

**Category:**Business & Economics

**Page:**768

**View:**1037

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# Search Results for: probability-and-statistics-for-engineering-and-the-sciences

**Author**: Jay L. Devore

**Publisher:** Cengage Learning

**ISBN:** 1305465326

**Category:** Business & Economics

**Page:** 768

**View:** 1037

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.

**Author**: Sheldon M. Ross

**Publisher:** Academic Press

**ISBN:** 0123948428

**Category:** Mathematics

**Page:** 686

**View:** 9475

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.

**Author**: Jay Devore

**Publisher:** Cengage Learning

**ISBN:** 0495557447

**Category:** Mathematics

**Page:** 768

**View:** 5644

This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. This proven, accurate book and its excellent examples evidence Jay Devore’s reputation as an outstanding author and leader in the academic community. Devore emphasizes concepts, models, methodology, and applications as opposed to rigorous mathematical development and derivations. Through the use of lively and realistic examples, students go beyond simply learning about statistics-they actually put the methods to use. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

**Author**: Anthony J. Hayter

**Publisher:** Cengage Learning

**ISBN:** 1111827044

**Category:** Mathematics

**Page:** 864

**View:** 7912

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.

**Author**: Jay L. Devore

**Publisher:** Duxbury Press

**ISBN:** 9780840065391

**Category:** Mathematics

**Page:** 222

**View:** 5572

Go beyond the answers--see what it takes to get there and improve your grade! This manual provides worked-out, step-by-step solutions to all of the odd-numbered problems in the text, giving you the information you need to truly understand how these problems are solved.

**Author**: Jay L. Devore,Elizabeth M. Eltinge

**Publisher:** Wadsworth Publishing Company

**ISBN:** 9780534242657

**Category:** Mathematical statistics

**Page:** 183

**View:** 4823

This text emphasizes models, methodology, and applications rather than rigorous mathematical development and theory. It uses real data in both exercise sets and examples.

**Author**: Jay Devore

**Publisher:** Cengage Learning

**ISBN:** 0495382175

**Category:** Mathematics

**Page:** 768

**View:** 3551

This market-leading text provides a comprehensive introduction to probability and statistics for engineering students in all specialties. This proven, accurate book and its excellent examples evidence Jay Devore’s reputation as an outstanding author and leader in the academic community. Devore emphasizes concepts, models, methodology, and applications as opposed to rigorous mathematical development and derivations. Through the use of lively and realistic examples, students go beyond simply learning about statistics-they actually put the methods to use. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.
*Manual*

**Author**: Jay L DeVore

**Publisher:** Thomson

**ISBN:** 9780534068295

**Category:** Mathematical statistics

**Page:** 206

**View:** 6175

**Author**: Julie Ann Seely

**Publisher:** Brooks/Cole Publishing Company

**ISBN:** 9780534399344

**Category:** Mathematics

**Page:** 311

**View:** 5855

The student solutions manual contains the worked out solutions to all odd numbered problems in the book.

**Author**: Jay L. Devore,Nicholas R. Farnum,Jimmy A. Doi

**Publisher:** Cengage Learning

**ISBN:** 1285972422

**Category:** Mathematics

**Page:** 656

**View:** 6647

This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS is ideal for one-term courses that cover probability only to the extent that it is needed for inference. The authors emphasize application of methods to real problems, with real examples throughout. The text is designed to meet ABET standards and has been updated to reflect the most current methodology and practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

**Author**: Matthew A. Carlton

**Publisher:** Brooks/Cole

**ISBN:** 9780495382195

**Category:** Mathematics

**Page:** 283

**View:** 1755

Check your work-and your understanding-with this manual, which provides worked-out solutions to the odd-numbered problems in the text.

**Author**: Sheldon M. Ross

**Publisher:** Academic Press

**ISBN:** 0080919421

**Category:** Science

**Page:** 30

**View:** 8116

Introduction to Probability and Statistics for Engineers and Scientists, Student Solutions Manual

**Author**: Edward R. Dougherty

**Publisher:** N.A

**ISBN:** N.A

**Category:** Mathematics

**Page:** 800

**View:** 6865

**Author**: Ronald E. Walpole,Raymond H. Myers,Sharon L. Myers

**Publisher:** Pearson College Division

**ISBN:** 9780321783738

**Category:** Mathematics

**Page:** 467

**View:** 8220

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.

**Author**: Allen B. Downey

**Publisher:** O'Reilly Germany

**ISBN:** 3868993436

**Category:** Computers

**Page:** 160

**View:** 6378

Wenn Sie programmieren können, beherrschen Sie bereits Techniken, um aus Daten Wissen zu extrahieren. Diese kompakte Einführung in die Statistik zeigt Ihnen, wie Sie rechnergestützt, anstatt auf mathematischem Weg Datenanalysen mit Python durchführen können. Praktischer Programmier-Workshop statt grauer Theorie: Das Buch führt Sie anhand eines durchgängigen Fallbeispiels durch eine vollständige Datenanalyse -- von der Datensammlung über die Berechnung statistischer Kennwerte und Identifikation von Mustern bis hin zum Testen statistischer Hypothesen. Gleichzeitig werden Sie mit statistischen Verteilungen, den Regeln der Wahrscheinlichkeitsrechnung, Visualisierungsmöglichkeiten und vielen anderen Arbeitstechniken und Konzepten vertraut gemacht. Statistik-Konzepte zum Ausprobieren: Entwickeln Sie über das Schreiben und Testen von Code ein Verständnis für die Grundlagen von Wahrscheinlichkeitsrechnung und Statistik: Überprüfen Sie das Verhalten statistischer Merkmale durch Zufallsexperimente, zum Beispiel indem Sie Stichproben aus unterschiedlichen Verteilungen ziehen. Nutzen Sie Simulationen, um Konzepte zu verstehen, die auf mathematischem Weg nur schwer zugänglich sind. Lernen Sie etwas über Themen, die in Einführungen üblicherweise nicht vermittelt werden, beispielsweise über die Bayessche Schätzung. Nutzen Sie Python zur Bereinigung und Aufbereitung von Rohdaten aus nahezu beliebigen Quellen. Beantworten Sie mit den Mitteln der Inferenzstatistik Fragestellungen zu realen Daten.

**Author**: Matthew A. Carlton,Jay L. Devore

**Publisher:** Springer

**ISBN:** 3319524011

**Category:** Mathematics

**Page:** 643

**View:** 1452

This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8 – available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise). For a year-long course, core chapters (1-4) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a self-contained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations.

**Author**: Bhisham C. Gupta,Irwin Guttman

**Publisher:** John Wiley & Sons

**ISBN:** 1118522206

**Category:** Mathematics

**Page:** 896

**View:** 6440

Introducing the tools of statistics and probabilityfrom the ground up An understanding of statistical tools is essential for engineersand scientists who often need to deal with data analysis over thecourse of their work. Statistics and Probability withApplications for Engineers and Scientists walks readers througha wide range of popular statistical techniques, explainingstep-by-step how to generate, analyze, and interpret data fordiverse applications in engineering and the natural sciences. Unique among books of this kind, Statistics and Probabilitywith Applications for Engineers and Scientists coversdescriptive statistics first, then goes on to discuss thefundamentals of probability theory. Along with case studies,examples, and real-world data sets, the book incorporates clearinstructions on how to use the statistical packages Minitab®and Microsoft® Office Excel® to analyze various datasets. The book also features: • Detailed discussions on sampling distributions,statistical estimation of population parameters, hypothesistesting, reliability theory, statistical quality control includingPhase I and Phase II control charts, and process capabilityindices • A clear presentation of nonparametric methods andsimple and multiple linear regression methods, as well as a briefdiscussion on logistic regression method • Comprehensive guidance on the design of experiments,including randomized block designs, one- and two-way layoutdesigns, Latin square designs, random effects and mixed effectsmodels, factorial and fractional factorial designs, and responsesurface methodology • A companion website containing data sets for Minitaband Microsoft Office Excel, as well as JMP ® routines andresults Assuming no background in probability and statistics,Statistics and Probability with Applications for Engineers andScientists features a unique, yet tried-and-true, approach thatis ideal for all undergraduate students as well as statisticalpractitioners who analyze and illustrate real-world data inengineering and the natural sciences.
*principles and applications for engineering and the computing sciences*

**Author**: Janet Susan Milton,Jesse C. Arnold

**Publisher:** McGraw-Hill Science/Engineering/Math

**ISBN:** 9780072468366

**Category:** Business & Economics

**Page:** 798

**View:** 3446

This well-respected text is designed for the first course in probability and statistics taken by students majoring in Engineering and the Computing Sciences. The prerequisite is one year of calculus. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with only a calculus background. They explore the practical implications of the formal results to problem-solving so students gain an understanding of the logic behind the techniques as well as practice in using them. The examples, exercises, and applications were chosen specifically for students in engineering and computer science and include opportunities for real data analysis.

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