Applied Statistics And Probability For Engineers 7th Edition Asia Edition
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| Author | : Douglas C. Montgomery |
| Publisher | : Wiley |
| Total Pages | : 0 |
| Release | : 2005-09-02 |
| Genre | : Technology & Engineering |
| ISBN | : 9780471735564 |
* More Motivation - A completely revised chapter 1 gets students motivated right from the beginning. * Revised Probability Topics - The authors have revised and enhanced probability topics to promote even easier understanding. * Chapter Reorganization - Chapters on hypothesis testing and confidence intervals have been reorganized and rewritten. There is now expanded treatment of confidence intervals, prediction intervals, and tolerance intervals. * Real Engineering Applications - Treatment of all topics is oriented towards real engineering applications. In the probability chapters, the authors do not emphasize counting methods or artificial applications such as gambling. * Real Data, Real Engineering Situations - Examples and exercises throughout text use real data and real engineering situations. This motivates students to learn new concepts and gives them a taste of practical engineering experience. Use of the Computer - Computer usage is closely integrated into the text and homework exercises.
| Author | : Ronald E. Walpole |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2017 |
| Genre | : Engineering |
| ISBN | : 9780134115856 |
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. Also available with MyStatLab MyStatLab(tm) 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. Note: You are purchasing a standalone product; MyLab(tm) & Mastering(tm) does not come packaged with this content. Students, if interested in purchasing this title with MyLab & Mastering, ask your instructor for the correct package ISBN and Course ID. Instructors, contact your Pearson representative for more information. If you would like to purchase both the physical text and MyLab & Mastering, search for: 0134468910 / 9780134468914 Probability & Statistics for Engineers & Scientists, MyStatLab Update with MyStatLab plus Pearson eText -- Access Card Package 9/e Package consists of: 0134115856 / 9780134115856 Probability & Statistics for Engineers & Scientists, MyStatLab Update 0321847997 / 9780321847997 My StatLab Glue-in Access Card 032184839X / 9780321848390 MyStatLab Inside Sticker for Glue-In Packages
| Author | : Kandethody M. Ramachandran |
| Publisher | : Elsevier |
| Total Pages | : 825 |
| Release | : 2014-09-14 |
| Genre | : Mathematics |
| ISBN | : 012417132X |
Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner.This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students.Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. - Step-by-step procedure to solve real problems, making the topic more accessible - Exercises blend theory and modern applications - Practical, real-world chapter projects - Provides an optional section in each chapter on using Minitab, SPSS and SAS commands - Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods
| Author | : Douglas C. Montgomery |
| Publisher | : Wiley Global Education |
| Total Pages | : 546 |
| Release | : 2011-08-24 |
| Genre | : Technology & Engineering |
| ISBN | : 111813799X |
Montgomery, Runger, and Hubele provide modern coverage of engineering statistics, focusing on how statistical tools are integrated into the engineering problem-solving process. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering experiments, and statistical process control. Developed with sponsorship from the National Science Foundation, this revision incorporates many insights from the authors teaching experience along with feedback from numerous adopters of previous editions.
| Author | : William DeCoursey |
| Publisher | : Elsevier |
| Total Pages | : 417 |
| Release | : 2003-05-14 |
| Genre | : Mathematics |
| ISBN | : 0080489753 |
Statistics and Probability for Engineering Applications provides a complete discussion of all the major topics typically covered in a college engineering statistics course. This textbook minimizes the derivations and mathematical theory, focusing instead on the information and techniques most needed and used in engineering applications. It is filled with practical techniques directly applicable on the job. Written by an experienced industry engineer and statistics professor, this book makes learning statistical methods easier for today's student. This book can be read sequentially like a normal textbook, but it is designed to be used as a handbook, pointing the reader to the topics and sections pertinent to a particular type of statistical problem. Each new concept is clearly and briefly described, whenever possible by relating it to previous topics. Then the student is given carefully chosen examples to deepen understanding of the basic ideas and how they are applied in engineering. The examples and case studies are taken from real-world engineering problems and use real data. A number of practice problems are provided for each section, with answers in the back for selected problems. This book will appeal to engineers in the entire engineering spectrum (electronics/electrical, mechanical, chemical, and civil engineering); engineering students and students taking computer science/computer engineering graduate courses; scientists needing to use applied statistical methods; and engineering technicians and technologists. * Filled with practical techniques directly applicable on the job* Contains hundreds of solved problems and case studies, using real data sets* Avoids unnecessary theory
| Author | : Wolfgang Karl Härdle |
| Publisher | : Springer Nature |
| Total Pages | : 611 |
| Release | : |
| Genre | : |
| ISBN | : 3031638336 |
| Author | : Barbara Illowsky |
| Publisher | : |
| Total Pages | : 2106 |
| Release | : 2023-12-13 |
| Genre | : Mathematics |
| ISBN | : |
Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.
| Author | : Douglas C. Montgomery |
| Publisher | : Wiley Global Education |
| Total Pages | : 771 |
| Release | : 2019-11-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1119399297 |
Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process characterization, optimization, and acceptance sampling, while examination of the implementation process provides context to real-world applications. Emphasis on Six Sigma DMAIC (Define, Measure, Analyze, Improve and Control) provides a strategic problem-solving framework that can be applied across a variety of disciplines. Adopting a balanced approach to traditional and modern methods, this text includes coverage of SQC techniques in both industrial and non-manufacturing settings, providing fundamental knowledge to students of engineering, statistics, business, and management sciences. A strong pedagogical toolset, including multiple practice problems, real-world data sets and examples, and incorporation of Minitab statistics software, provides students with a solid base of conceptual and practical knowledge.
| Author | : Douglas C. Montgomery |
| Publisher | : Wiley |
| Total Pages | : 848 |
| Release | : 2017-12-18 |
| Genre | : Technology & Engineering |
| ISBN | : 9781119400301 |
Written by engineers, it uses a practical, applied approach that is more oriented to engineering than any other text available. Instead of a few engineering examples mixed in with examples from other fields, all of its unique problem sets reflect the types of situations encountered by engineers in their working lives.
| Author | : Gareth James |
| Publisher | : Springer Nature |
| Total Pages | : 617 |
| Release | : 2023-08-01 |
| Genre | : Mathematics |
| ISBN | : 3031387473 |
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
