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| engineering mathematics and statistics: Engineering Mathematics and Statistics Nicholas P. Cheremisinoff, Louise Ferrante, 1989-07-10 This pocket handbook is intended as a handy reference guide for engineers, scientists and students on widely used mathematical relationships, statistical formulas and problem-solving methods, including illustrated examples for problem-solving methods. |
| engineering mathematics and statistics: Engineering Statistics Douglas C. Montgomery, George C. Runger, Norma F. Hubele, 2011-08-24 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. |
| engineering mathematics and statistics: Statistics in Engineering Andrew Metcalfe, David Green, Tony Greenfield, Mayhayaudin Mansor, Andrew Smith, Jonathan Tuke, 2019-01-25 Engineers are expected to design structures and machines that can operate in challenging and volatile environments, while allowing for variation in materials and noise in measurements and signals. Statistics in Engineering, Second Edition: With Examples in MATLAB and R covers the fundamentals of probability and statistics and explains how to use these basic techniques to estimate and model random variation in the context of engineering analysis and design in all types of environments. The first eight chapters cover probability and probability distributions, graphical displays of data and descriptive statistics, combinations of random variables and propagation of error, statistical inference, bivariate distributions and correlation, linear regression on a single predictor variable, and the measurement error model. This leads to chapters including multiple regression; comparisons of several means and split-plot designs together with analysis of variance; probability models; and sampling strategies. Distinctive features include: All examples based on work in industry, consulting to industry, and research for industry Examples and case studies include all engineering disciplines Emphasis on probabilistic modeling including decision trees, Markov chains and processes, and structure functions Intuitive explanations are followed by succinct mathematical justifications Emphasis on random number generation that is used for stochastic simulations of engineering systems, demonstration of key concepts, and implementation of bootstrap methods for inference Use of MATLAB and the open source software R, both of which have an extensive range of statistical functions for standard analyses and also enable programing of specific applications Use of multiple regression for times series models and analysis of factorial and central composite designs Inclusion of topics such as Weibull analysis of failure times and split-plot designs that are commonly used in industry but are not usually included in introductory textbooks Experiments designed to show fundamental concepts that have been tested with large classes working in small groups Website with additional materials that is regularly updated Andrew Metcalfe, David Green, Andrew Smith, and Jonathan Tuke have taught probability and statistics to students of engineering at the University of Adelaide for many years and have substantial industry experience. Their current research includes applications to water resources engineering, mining, and telecommunications. Mahayaudin Mansor worked in banking and insurance before teaching statistics and business mathematics at the Universiti Tun Abdul Razak Malaysia and is currently a researcher specializing in data analytics and quantitative research in the Health Economics and Social Policy Research Group at the Australian Centre for Precision Health, University of South Australia. Tony Greenfield, formerly Head of Process Computing and Statistics at the British Iron and Steel Research Association, is a statistical consultant. He has been awarded the Chambers Medal for outstanding services to the Royal Statistical Society; the George Box Medal by the European Network for Business and Industrial Statistics for Outstanding Contributions to Industrial Statistics; and the William G. Hunter Award by the American Society for Quality. |
| engineering mathematics and statistics: Engineering Mathematics and Statistics Nicholas P Cheremisinoff, 2018 |
| engineering mathematics and statistics: Statistical Methods for Engineering and Sciences H. C. Taneja, 2013-12-30 The present book is meant for the first-year students of various universities. Engineering educationists feel that first-year students of all disciplines must have an elementary and general idea about various branches of electronics. Spread in sixteen chapters, the book broadly discusses. |
| engineering mathematics and statistics: Introduction to Probability and Statistics for Engineers Milan Holický, 2013-08-04 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. |
| engineering mathematics and statistics: Statistics for Engineers Hartmut Schiefer, Felix Schiefer, 2021-04-16 This book describes how statistical methods can be effectively applied in the work of an engineer in terms that can be readily understood. Application of these methods enables the effort involved in experiments to be reduced, the results of these experiments to be fully evaluated, and statistically sound statements to be made as a result. Products can be developed more efficiently and manufactured more cost-effectively, not to mention with greater process reliability. The overarching aim is to save time, money, and materials. From the examples provided, the nature of the practical application can be clearly grasped in each case. This book is a translation of the original German 1st edition Statistik für Ingenieure by Hartmut Schiefer and Felix Schiefer, published by Springer Fachmedien Wiesbaden GmbH, part of Springer Nature in 2018. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). The present version has been revised technically and linguistically by the authors in collaboration with a professional translator. Springer Nature works continuously to further the development of tools for the production of books and on the related technologies to support the authors. |
| engineering mathematics and statistics: Engineering Mathematics Volume - III (Statistical and Numerical Methods) (For 1st Year - 2nd Semester of JNTU, Hyderabad) Iyenger T.K.V./ Gandhi, Krishna B./ Ranganatham S. & Prasad M.V.S.S.N., Engineering Mathematics |
| engineering mathematics and statistics: Fundamentals of Probability and Statistics for Engineers T. T. Soong, 2004-06-25 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. |
| engineering mathematics and statistics: Engineering Mathematics Through Applications Kuldeep Singh, 2019-12-13 This popular, world-wide selling textbook teaches engineering mathematics in a step-by-step fashion and uniquely through engineering examples and exercises which apply the techniques right from their introduction. This contextual use of mathematics is highly motivating, as with every topic and each new page students see the importance and relevance of mathematics in engineering. The examples are taken from mechanics, aerodynamics, electronics, engineering, fluid dynamics and other areas. While being general and accessible for all students, they also highlight how mathematics works in any individual's engineering discipline. The material is often praised for its careful pace, and the author pauses to ask questions to keep students reflecting. Proof of mathematical results is kept to a minimum. Instead the book develops learning by investigating results, observing patterns, visualizing graphs and answering questions using technology. This textbook is ideal for first year undergraduates and those on pre-degree courses in Engineering (all disciplines) and Science. New to this Edition: - Fully revised and improved on the basis of student feedback - New sections - More examples, more exam questions - Vignettes and photos of key mathematicians |
| engineering mathematics and statistics: Advanced Engineering Mathematics Dennis G. Zill, Michael R. Cullen, 2006 Thoroughly Updated, Zill'S Advanced Engineering Mathematics, Third Edition Is A Compendium Of Many Mathematical Topics For Students Planning A Career In Engineering Or The Sciences. A Key Strength Of This Text Is Zill'S Emphasis On Differential Equations As Mathematical Models, Discussing The Constructs And Pitfalls Of Each. The Third Edition Is Comprehensive, Yet Flexible, To Meet The Unique Needs Of Various Course Offerings Ranging From Ordinary Differential Equations To Vector Calculus. Numerous New Projects Contributed By Esteemed Mathematicians Have Been Added. Key Features O The Entire Text Has Been Modernized To Prepare Engineers And Scientists With The Mathematical Skills Required To Meet Current Technological Challenges. O The New Larger Trim Size And 2-Color Design Make The Text A Pleasure To Read And Learn From. O Numerous NEW Engineering And Science Projects Contributed By Top Mathematicians Have Been Added, And Are Tied To Key Mathematical Topics In The Text. O Divided Into Five Major Parts, The Text'S Flexibility Allows Instructors To Customize The Text To Fit Their Needs. The First Eight Chapters Are Ideal For A Complete Short Course In Ordinary Differential Equations. O The Gram-Schmidt Orthogonalization Process Has Been Added In Chapter 7 And Is Used In Subsequent Chapters. O All Figures Now Have Explanatory Captions. Supplements O Complete Instructor'S Solutions: Includes All Solutions To The Exercises Found In The Text. Powerpoint Lecture Slides And Additional Instructor'S Resources Are Available Online. O Student Solutions To Accompany Advanced Engineering Mathematics, Third Edition: This Student Supplement Contains The Answers To Every Third Problem In The Textbook, Allowing Students To Assess Their Progress And Review Key Ideas And Concepts Discussed Throughout The Text. ISBN: 0-7637-4095-0 |
| engineering mathematics and statistics: Mathematical and Statistical Applications in Life Sciences and Engineering Avishek Adhikari, Mahima Ranjan Adhikari, Yogendra Prasad Chaubey, 2017-12-06 The book includes articles from eminent international scientists discussing a wide spectrum of topics of current importance in mathematics and statistics and their applications. It presents state-of-the-art material along with a clear and detailed review of the relevant topics and issues concerned. The topics discussed include message transmission, colouring problem, control of stochastic structures and information dynamics, image denoising, life testing and reliability, survival and frailty models, analysis of drought periods, prediction of genomic profiles, competing risks, environmental applications and chronic disease control. It is a valuable resource for researchers and practitioners in the relevant areas of mathematics and statistics. |
| engineering mathematics and statistics: Advanced Engineering Mathematics Michael Greenberg, 2013-09-20 Appropriate for one- or two-semester Advanced Engineering Mathematics courses in departments of Mathematics and Engineering. This clear, pedagogically rich book develops a strong understanding of the mathematical principles and practices that today's engineers and scientists need to know. Equally effective as either a textbook or reference manual, it approaches mathematical concepts from a practical-use perspective making physical applications more vivid and substantial. Its comprehensive instructional framework supports a conversational, down-to-earth narrative style offering easy accessibility and frequent opportunities for application and reinforcement. |
| engineering mathematics and statistics: Methods of Mathematics Applied to Calculus, Probability, and Statistics Richard W. Hamming, 2012-06-28 This 4-part treatment begins with algebra and analytic geometry and proceeds to an exploration of the calculus of algebraic functions and transcendental functions and applications. 1985 edition. Includes 310 figures and 18 tables. |
| engineering mathematics and statistics: Statistics and Data Analysis for Financial Engineering David Ruppert, David S. Matteson, 2015-04-21 The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest. |
| engineering mathematics and statistics: Fundamentals of Probability and Statistics for Engineers T. T. Soong, 2004-03-26 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. |
| engineering mathematics and statistics: Examples and Problems in Mathematical Statistics Shelemyahu Zacks, 2013-12-17 Provides the necessary skills to solve problems in mathematical statistics through theory, concrete examples, and exercises With a clear and detailed approach to the fundamentals of statistical theory, Examples and Problems in Mathematical Statistics uniquely bridges the gap between theory andapplication and presents numerous problem-solving examples that illustrate the relatednotations and proven results. Written by an established authority in probability and mathematical statistics, each chapter begins with a theoretical presentation to introduce both the topic and the important results in an effort to aid in overall comprehension. Examples are then provided, followed by problems, and finally, solutions to some of the earlier problems. In addition, Examples and Problems in Mathematical Statistics features: Over 160 practical and interesting real-world examples from a variety of fields including engineering, mathematics, and statistics to help readers become proficient in theoretical problem solving More than 430 unique exercises with select solutions Key statistical inference topics, such as probability theory, statistical distributions, sufficient statistics, information in samples, testing statistical hypotheses, statistical estimation, confidence and tolerance intervals, large sample theory, and Bayesian analysis Recommended for graduate-level courses in probability and statistical inference, Examples and Problems in Mathematical Statistics is also an ideal reference for applied statisticians and researchers. |
| engineering mathematics and statistics: Probability Theory and Mathematical Statistics for Engineers Paolo L. Gatti, 2004-11-10 Probability Theory and Statistical Methods for Engineers brings together probability theory with the more practical applications of statistics, bridging theory and practice. It gives a series of methods or recipes which can be applied to specific problems. This book is essential reading for practicing engineers who need a sound background knowledge of probabilistic and statistical concepts and methods of analysis for their everyday work. It is also a useful guide for graduate engineering students. |
| engineering mathematics and statistics: Engineering Mathematics K. A. Stroud, 2001 A groundbreaking and comprehensive reference that's been a bestseller since 1970, this new edition provides a broad mathematical survey and covers a full range of topics from the very basic to the advanced. For the first time, a personal tutor CD-ROM is included. |
| engineering mathematics and statistics: Mathematics in Engineering Sciences Mangey Ram, 2019-09-09 This book includes research studies, novel theory, as well as new methodology and applications in mathematics and management sciences. The book will provide a comprehensive range of mathematics applied to engineering areas for different tasks. It will offer an international perspective and a bridge between classical theory and new methodology in many areas, along with real-life applications. Features Offers solutions to multi-objective transportation problem under cost reliability using utility function Presents optimization techniques to support eco-efficiency assessment in manufacturing processes Covers distance-based function approach for optimal design of engineering processes with multiple quality characteristics Provides discrete time sliding mode control for non-linear networked control systems Discusses second law of thermodynamics as instruments for optimizing fluid dynamic systems and aerodynamic systems |
| engineering mathematics and statistics: Probability and Statistics for Engineers Richard L. Scheaffer, James T. McClave, 1995 Designed to teach engineers to think statistically so that data can be collected and used intelligently in solving real problems, this text is intended for calculus-based, one-semester introduction to engineering statistics courses. Although traditional topics are covered, this edition takes a modern, data-oriented, problem-solving, process-improvement view of engineering statistics. The emphasis is on collecting good data through sample surveys and experiments and on applying it to real problems. |
| engineering mathematics and statistics: Applied Engineering Mathematics Brian Vick, 2020-05-05 Undergraduate engineering students need good mathematics skills. This textbook supports this need by placing a strong emphasis on visualization and the methods and tools needed across the whole of engineering. The visual approach is emphasized, and excessive proofs and derivations are avoided. The visual images explain and teach the mathematical methods. The book’s website provides dynamic and interactive codes in Mathematica to accompany the examples for the reader to explore on their own with Mathematica or the free Computational Document Format player, and it provides access for instructors to a solutions manual. Strongly emphasizes a visual approach to engineering mathematics Written for years 2 to 4 of an engineering degree course Website offers support with dynamic and interactive Mathematica code and instructor’s solutions manual Brian Vick is an associate professor at Virginia Tech in the United States and is a longtime teacher and researcher. His style has been developed from teaching a variety of engineering and mathematical courses in the areas of heat transfer, thermodynamics, engineering design, computer programming, numerical analysis, and system dynamics at both undergraduate and graduate levels. eResource material is available for this title at www.crcpress.com/9780367432768. |
| engineering mathematics and statistics: Springer Handbook of Engineering Statistics Hoang Pham, 2006 In today’s global and highly competitive environment, continuous improvement in the processes and products of any field of engineering is essential for survival. This book gathers together the full range of statistical techniques required by engineers from all fields. It will assist them to gain sensible statistical feedback on how their processes or products are functioning and to give them realistic predictions of how these could be improved. The handbook will be essential reading for all engineers and engineering-connected managers who are serious about keeping their methods and products at the cutting edge of quality and competitiveness. |
| engineering mathematics and statistics: Modern Mathematical Statistics with Applications Jay L. Devore, Kenneth N. Berk, Matthew A. Carlton, 2021-04-29 This 3rd edition of Modern Mathematical Statistics with Applications tries to strike a balance between mathematical foundations and statistical practice. The book provides a clear and current exposition of statistical concepts and methodology, including many examples and exercises based on real data gleaned from publicly available sources. Here is a small but representative selection of scenarios for our examples and exercises based on information in recent articles: Use of the “Big Mac index” by the publication The Economist as a humorous way to compare product costs across nations Visualizing how the concentration of lead levels in cartridges varies for each of five brands of e-cigarettes Describing the distribution of grip size among surgeons and how it impacts their ability to use a particular brand of surgical stapler Estimating the true average odometer reading of used Porsche Boxsters listed for sale on www.cars.com Comparing head acceleration after impact when wearing a football helmet with acceleration without a helmet Investigating the relationship between body mass index and foot load while running The main focus of the book is on presenting and illustrating methods of inferential statistics used by investigators in a wide variety of disciplines, from actuarial science all the way to zoology. It begins with a chapter on descriptive statistics that immediately exposes the reader to the analysis of real data. The next six chapters develop the probability material that facilitates the transition from simply describing data to drawing formal conclusions based on inferential methodology. Point estimation, the use of statistical intervals, and hypothesis testing are the topics of the first three inferential chapters. The remainder of the book explores the use of these methods in a variety of more complex settings. This edition includes many new examples and exercises as well as an introduction to the simulation of events and probability distributions. There are more than 1300 exercises in the book, ranging from very straightforward to reasonably challenging. Many sections have been rewritten with the goal of streamlining and providing a more accessible exposition. Output from the most common statistical software packages is included wherever appropriate (a feature absent from virtually all other mathematical statistics textbooks). The authors hope that their enthusiasm for the theory and applicability of statistics to real world problems will encourage students to pursue more training in the discipline. |
| engineering mathematics and statistics: Advanced Engineering Mathematics Dean G. Duffy, 2022-03-23 Through four previous editions of Advanced Engineering Mathematics with MATLAB, the author presented a wide variety of topics needed by today's engineers. The fifth edition of that book, available now, has been broken into two parts: topics currently needed in mathematics courses and a new stand-alone volume presenting topics not often included in these courses and consequently unknown to engineering students and many professionals. The overall structure of this new book consists of two parts: transform methods and random processes. Built upon a foundation of applied complex variables, the first part covers advanced transform methods, as well as z-transforms and Hilbert transforms--transforms of particular interest to systems, communication, and electrical engineers. This portion concludes with Green's function, a powerful method of analyzing systems. The second portion presents random processes--processes that more accurately model physical and biological engineering. Of particular interest is the inclusion of stochastic calculus. The author continues to offer a wealth of examples and applications from the scientific and engineering literature, a highlight of his previous books. As before, theory is presented first, then examples, and then drill problems. Answers are given in the back of the book. This book is all about the future: The purpose of this book is not only to educate the present generation of engineers but also the next. The main strength is the text is written from an engineering perspective. The majority of my students are engineers. The physical examples are related to problems of interest to the engineering students. --Lea Jenkins, Clemson University |
| engineering mathematics and statistics: Engineering Mathematics S.R. Koneru, 2002-11 This book incorporates in one volume the material covered in the mathematics course of undergraduate programmes in engineering and technology. The topics discussed include sequences and series, mean value theorems, evolutes, functions of several variables, solutions of ordinary and partial differential equations, Laplace, Fourier and Z-transform with their applications. |
| engineering mathematics and statistics: Advanced Engineering Mathematics with Mathematica Edward B. Magrab, 2020-02-26 Advanced Engineering Mathematics with Mathematica® presents advanced analytical solution methods that are used to solve boundary-value problems in engineering and integrates these methods with Mathematica® procedures. It emphasizes the Sturm–Liouville system and the generation and application of orthogonal functions, which are used by the separation of variables method to solve partial differential equations. It introduces the relevant aspects of complex variables, matrices and determinants, Fourier series and transforms, solution techniques for ordinary differential equations, the Laplace transform, and procedures to make ordinary and partial differential equations used in engineering non-dimensional. To show the diverse applications of the material, numerous and widely varied solved boundary value problems are presented. |
| engineering mathematics and statistics: Engineering Mathematics Semester - Iii (engineering Statistics) A.s. Sharma, 2009 |
| engineering mathematics and statistics: Mathematics for Mechanical Engineers Frank Kreith, William F. Ames, George Cain, Y. L. Tong, W. Glenn Steele, Hugh W. Coleman, Richard L. Kautz, Dan M. Frangopol, Paul Norton, 1999-12-06 Mathematics for Mechanical Engineers gives mechanical engineers convenient access to the essential problem solving tools that they use each day. It covers applications employed in many different facets of mechanical engineering, from basic through advanced, to ensure that you will easily find answers you need in this handy guide. For the engineer venturing out of familiar territory, the chapters cover fundamentals like physical constants, derivatives, integrals, Fourier transforms, Bessel functions, and Legendre functions. For the experts, it includes thorough sections on the more advanced topics of partial differential equations, approximation methods, and numerical methods, often used in applications. The guide reviews statistics for analyzing engineering data and making inferences, so professionals can extract useful information even with the presence of randomness and uncertainty. The convenient Mathematics for Mechanical Engineers is an indispensable summary of mathematics processes needed by engineers. |
| engineering mathematics and statistics: Advanced Engineering Mathematics Erwin Kreyszig, 2019-01-03 |
| engineering mathematics and statistics: Advanced Engineering Mathematics K. A. Stroud, Dexter J. Booth, 2011 A worldwide bestseller renowned for its effective self-instructional pedagogy. |
| engineering mathematics and statistics: Mathematics for Engineering W Bolton, 2012-08-06 Mathematics for Engineering has been carefully designed to provide a maths course for a wide ability range, and does not go beyond the requirements of Advanced GNVQ. It is an ideal text for any pre-degree engineering course where students require revision of the basics and plenty of practice work. Bill Bolton introduces the key concepts through examples set firmly in engineering contexts, which students will find relevant and motivating. The second edition has been carefully matched to the Curriculum 2000 Advanced GNVQ units: Applied Mathematics in Engineering (compulsory unit 5) Further Mathematics for Engineering (Edexcel option unit 13) Further Applied Mathematics for Engineering (AQA / City & Guilds option unit 25) A new introductory section on number and mensuration has been added, as well as a new section on series and some further material on applications of differentiation and definite integration. Bill Bolton is a leading author of college texts in engineering and other technical subjects. As well as being a lecturer for many years, he has also been Head of Research, Development and Monitoring at BTEC and acted as a consultant for the Further Education Unit. |
| engineering mathematics and statistics: Mathematics-II (Probability and Statistics) Bhui, Bikas Chandra & Chatterjee Dipak, Mathematics-II (Probability and Statistics) for the paper BSC-106 of the latest AICTE syllabus has been written for the second semester engineering students of Indian universities. Paper BSC-106 is for the CS&E stream. The book has been planned with utmost care in the exposition of concepts, choice of illustrative examples, and also in sequencing of topics. The language is simple, yet accurate. A large number of worked-out problems have been included to familiarize the students with the techniques to solving them, and to instil confidence. Authors’ long experience of teaching various grades of students has helped in laying proper emphasis on various techniques of solving difficult problems. |
| engineering mathematics and statistics: Introductory Statistics and Analytics Peter C. Bruce, 2015-01-08 Concise, thoroughly class-tested primer that features basic statistical concepts in the concepts in the context of analytics, resampling, and the bootstrap A uniquely developed presentation of key statistical topics, Introductory Statistics and Analytics: A Resampling Perspective provides an accessible approach to statistical analytics, resampling, and the bootstrap for readers with various levels of exposure to basic probability and statistics. Originally class-tested at one of the first online learning companies in the discipline, www.statistics.com, the book primarily focuses on applications of statistical concepts developed via resampling, with a background discussion of mathematical theory. This feature stresses statistical literacy and understanding, which demonstrates the fundamental basis for statistical inference and demystifies traditional formulas. The book begins with illustrations that have the essential statistical topics interwoven throughout before moving on to demonstrate the proper design of studies. Meeting all of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) requirements for an introductory statistics course, Introductory Statistics and Analytics: A Resampling Perspective also includes: Over 300 “Try It Yourself” exercises and intermittent practice questions, which challenge readers at multiple levels to investigate and explore key statistical concepts Numerous interactive links designed to provide solutions to exercises and further information on crucial concepts Linkages that connect statistics to the rapidly growing field of data science Multiple discussions of various software systems, such as Microsoft Office Excel®, StatCrunch, and R, to develop and analyze data Areas of concern and/or contrasting points-of-view indicated through the use of “Caution” icons Introductory Statistics and Analytics: A Resampling Perspective is an excellent primary textbook for courses in preliminary statistics as well as a supplement for courses in upper-level statistics and related fields, such as biostatistics and econometrics. The book is also a general reference for readers interested in revisiting the value of statistics. |
| engineering mathematics and statistics: Engineering Mathematics C W. Evans, 2019-03-04 The programmed approach, established in the first two editions is maintained in the third and it provides a sound foundation from which the student can build a solid engineering understanding. This edition has been modified to reflect the changes in the syllabuses which students encounter before beginning undergraduate studies. The first two chapters include material that assumes the reader has little previous experience in maths. Written by CHarles Evans who lectures at the University of Portsmouth and has been teaching engineering and applied mathematics for more than 25 years. This text provides one of the essential tools for both undergraduate students and professional engineers. |
| engineering mathematics and statistics: Statistical Software Engineering National Research Council, Division on Engineering and Physical Sciences, Commission on Physical Sciences, Mathematics, and Applications, Panel on Statistical Methods in Software Engineering, 1996-03-15 This book identifies challenges and opportunities in the development and implementation of software that contain significant statistical content. While emphasizing the relevance of using rigorous statistical and probabilistic techniques in software engineering contexts, it presents opportunities for further research in the statistical sciences and their applications to software engineering. It is intended to motivate and attract new researchers from statistics and the mathematical sciences to attack relevant and pressing problems in the software engineering setting. It describes the big picture, as this approach provides the context in which statistical methods must be developed. The book's survey nature is directed at the mathematical sciences audience, but software engineers should also find the statistical emphasis refreshing and stimulating. It is hoped that the book will have the effect of seeding the field of statistical software engineering by its indication of opportunities where statistical thinking can help to increase understanding, productivity, and quality of software and software production. |
| engineering mathematics and statistics: Probability Theory and Mathematical Statistics for Engineers V. S. Pugachev, 2014-06-28 Probability Theory and Mathematical Statistics for Engineers focuses on the concepts of probability theory and mathematical statistics for finite-dimensional random variables. The book underscores the probabilities of events, random variables, and numerical characteristics of random variables. Discussions focus on canonical expansions of random vectors, second-order moments of random vectors, generalization of the density concept, entropy of a distribution, direct evaluation of probabilities, and conditional probabilities. The text then examines projections of random vectors and their distributions, including conditional distributions of projections of a random vector, conditional numerical characteristics, and information contained in random variables. The book elaborates on the functions of random variables and estimation of parameters of distributions. Topics include frequency as a probability estimate, estimation of statistical characteristics, estimation of the expectation and covariance matrix of a random vector, and testing the hypotheses on the parameters of distributions. The text then takes a look at estimator theory and estimation of distributions. The book is a vital source of data for students, engineers, postgraduates of applied mathematics, and other institutes of higher technical education. |
| engineering mathematics and statistics: Mathematics Applied to Engineering and Management Mangey Ram, S.B. Singh, 2019-08-08 This book offers the latest research advances in the field of mathematics applications in engineering sciences and provides a reference with a theoretical and sound background, along with case studies. In recent years, mathematics has had an amazing growth in engineering sciences. It forms the common foundation of all engineering disciplines. This new book provides a comprehensive range of mathematics applied to various fields of engineering for different tasks in fields such as civil engineering, structural engineering, computer science, electrical engineering, among others. It offers articles that develop the applications of mathematics in engineering sciences, conveys the innovative research ideas, offers real-world utility of mathematics, and plays a significant role in the life of academics, practitioners, researchers, and industry leaders. Focuses on the latest research in the field of engineering applications Includes recent findings from various institutions Identifies the gaps in the knowledge of the field and provides the latest approaches Presents international studies and findings in modelling and simulation Offers various mathematical tools, techniques, strategies, and methods across different engineering fields |
| engineering mathematics and statistics: Probability, Statistics, and Decision for Civil Engineers Jack R Benjamin, C. Allin Cornell, 2014-07-16 This text covers the development of decision theory and related applications of probability. Extensive examples and illustrations cultivate students' appreciation for applications, including strength of materials, soil mechanics, construction planning, and water-resource design. Emphasis on fundamentals makes the material accessible to students trained in classical statistics and provides a brief introduction to probability. 1970 edition-- |
| engineering mathematics and statistics: Advanced Engineering Mathematics Lawrence Turyn, 2013-09-25 Beginning with linear algebra and later expanding into calculus of variations, Advanced Engineering Mathematics provides accessible and comprehensive mathematical preparation for advanced undergraduate and beginning graduate students taking engineering courses. This book offers a review of standard mathematics coursework while effectively integrating science and engineering throughout the text. It explores the use of engineering applications, carefully explains links to engineering practice, and introduces the mathematical tools required for understanding and utilizing software packages. Provides comprehensive coverage of mathematics used by engineering students Combines stimulating examples with formal exposition and provides context for the mathematics presented Contains a wide variety of applications and homework problems Includes over 300 figures, more than 40 tables, and over 1500 equations Introduces useful MathematicaTM and MATLAB® procedures Presents faculty and student ancillaries, including an online student solutions manual, full solutions manual for instructors, and full-color figure sides for classroom presentations Advanced Engineering Mathematics covers ordinary and partial differential equations, matrix/linear algebra, Fourier series and transforms, and numerical methods. Examples include the singular value decomposition for matrices, least squares solutions, difference equations, the z-transform, Rayleigh methods for matrices and boundary value problems, the Galerkin method, numerical stability, splines, numerical linear algebra, curvilinear coordinates, calculus of variations, Liapunov functions, controllability, and conformal mapping. This text also serves as a good reference book for students seeking additional information. It incorporates Short Takes sections, describing more advanced topics to readers, and Learn More about It sections with direct references for readers wanting more in-depth information. |
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