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Probability and Statistics for Engineers and Scientists

Probability and Statistics for Engineers and Scientists PDF Author: Ronald E. Walpole
Publisher:
ISBN: 9780134115856
Category : Engineering
Languages : en
Pages : 0

Book Description
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

Probability and Statistics for Engineers and Scientists

Probability and Statistics for Engineers and Scientists PDF Author: Ronald E. Walpole
Publisher:
ISBN: 9780134115856
Category : Engineering
Languages : en
Pages : 0

Book Description
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

Subject Guide to Books in Print

Subject Guide to Books in Print PDF Author:
Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 2118

Book Description


Probability and Statistics for Engineering and the Sciences

Probability and Statistics for Engineering and the Sciences PDF Author: Jay Devore
Publisher: Cengage Learning
ISBN: 9780495382171
Category : Mathematics
Languages : en
Pages : 768

Book Description
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.

Introduction to Statistics

Introduction to Statistics PDF Author: Ronald E. Walpole
Publisher:
ISBN:
Category :
Languages : en
Pages : 365

Book Description


The Publishers' Trade List Annual

The Publishers' Trade List Annual PDF Author:
Publisher:
ISBN:
Category : American literature
Languages : en
Pages : 828

Book Description


Mathematics Magazine

Mathematics Magazine PDF Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 354

Book Description


Mathematics for Machine Learning

Mathematics for Machine Learning PDF Author: Marc Peter Deisenroth
Publisher: Cambridge University Press
ISBN: 1108569323
Category : Computers
Languages : en
Pages : 392

Book Description
The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Books in Print

Books in Print PDF Author:
Publisher: Reed Reference Publishing
ISBN:
Category : Reference
Languages : en
Pages : 1740

Book Description
V. 1. Authors (A-D) -- v. 2. Authors (E-K) -- v. 3. Authors (L-R) -- v. 4. (S-Z) -- v. 5. Titles (A-D) -- v. 6. Titles (E-K) -- v. 7. Titles (L-Q) -- v. 8. Titles (R-Z) -- v. 9. Out of print, out of stock indefinitely -- v. 10. -- Publishers.

AMSTAT News

AMSTAT News PDF Author:
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 578

Book Description


Journal of the American Statistical Association

Journal of the American Statistical Association PDF Author: American Statistical Association
Publisher:
ISBN:
Category : Electronic journals
Languages : en
Pages : 962

Book Description
A scientific and educational journal not only for professional statisticians but also for economists, business executives, research directors, government officials, university professors, and others who are seriously interested in the application of statistical methods to practical problems, in the development of more useful methods, and in the improvement of basic statistical data.