Introductory Statistics and Analytics by Peter C. Bruce; Inbal YahavConcise, 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#65533;, 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.
Publication Date: 2014-12-03
Probability, Statistics, and Decision for Civil Engineers by Jack R. Benjamin; C. Allin CornellDesigned as a primary text for civil engineering courses, as a supplementary text for courses in other areas, or for self-study by practicing engineers, this text covers the development of decision theory and the applications of probability within the field. Extensive use of examples and illustrations helps readers develop an in-depth appreciation for the theory's applications, which include strength of materials, soil mechanics, construction planning, and water-resource design. A focus on fundamentals includes such subjects as Bayesian statistical decision theory, subjective probability, and utility theory. This makes the material accessible to engineers trained in classical statistics and also provides a brief elementary introduction to probability. The coverage also addresses in detail the methods for analyzing engineering economic decisions in the face of uncertainty. An Appendix of tables makes this volume particularly useful as a reference text.
Publication Date: 2014-07-16
Probability and Statistics for Scientists and Engineers by Rao V. DukkipatiCoverage of all course fundamentals in easy-to-understand methodology.Clarity in the presentation of concepts.Review questions, true/false, and fill in the blanks for each chapter.Over 230 fully solved problems with step-by-step solutions.Over 520 additional practice problems with answers.ABOUT THE BOOK:Probability and Statistics for Scientists and Engineers is designed as a supplement to an introductory undergraduate or graduate course for mathematics, science and engineering students of all disciplines. The text covers all major aspects of engineering statistics, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples and curve fitting, correlation, regression, chi-square tests, and analysis of variance. The book continues to maintain a student-friendly approach and numerical problem solving orientation. Presentations are limited to very basic topics to serve as an introduction to advance topics in those areas of discipline. The purpose of the book is to present the principles and concepts of Probability and Statistics as relevant to student learning.
Publication Date: 2011-02-01
Applications of Statistics and Probability in Civil Engineering by Michael Faber (Editor)Under the pressure of harsh environmental conditions and natural hazards, large parts of the world population are struggling to maintain their livelihoods. Population growth, increasing land utilization and shrinking natural resources have led to an increasing demand of improved efficiency of existing technologies and the development of new ones. Additionally, growing complexities of societal functionalities and interdependencies among infrastructures and urban habitats amplify consequences of malfunctions and failures. Malevolence, sustainable developments and climatic changes have more recently been added to the list of challenges. Over the last decades, substantial progress has been made in assessing and quantifying risks. However, with regard to the broader utilization of risk assessment as a means for societal strategic and operational planning, there is still a great need for further development. Applications of Statistics and Probability in Civil Engineering contains the proceedings of the 11th International Conference on Applications of Statistics and Probability in Civil Engineering (ICASP11, Zurich, Switzerland, 1-4 August 2011). The book focuses not only on the more traditional technical issues, but also emphasizes the societal context of the decision making problems including the interaction between stakeholders. This holistic perspective supports the enhanced and sustainable allocation of limited resources for the improvement of safety, environment and economy. The book is of interest to researchers and scientists working in the field of risk and reliability in engineering; to professionals and engineers, including insurance and consulting companies working with natural hazards, design, operation and maintenance of civil engineering and industrial facilities; and to decision makers and professionals in the public sector, including nongovernmental organisations responsible for risk management in the public domain, e.g. building authorities, the health and safety executives, the United Nations and the World Economic Forum."
Publication Date: 2011-07-19
Probability Concepts and Theory for Engineers by Harry SchwarzlanderA thorough introduction to the fundamentals of probability theory This book offers a detailed explanation of the basic models and mathematical principles used in applying probability theory to practical problems. It gives the reader a solid foundation for formulating and solving many kinds of probability problems for deriving additional results that may be needed in order to address more challenging questions, as well as for proceeding with the study of a wide variety of more advanced topics. Great care is devoted to a clear and detailed development of the 'conceptual model' which serves as the bridge between any real-world situation and its analysis by means of the mathematics of probability. Throughout the book, this conceptual model is not lost sight of. Random variables in one and several dimensions are treated in detail, including singular random variables, transformations, characteristic functions, and sequences. Also included are special topics not covered in many probability texts, such as fuzziness, entropy, spherically symmetric random variables, and copulas. Some special features of the book are: a unique step-by-step presentation organized into 86 topical Sections, which are grouped into six Parts over 200 diagrams augment and illustrate the text, which help speed the reader's comprehension of the material short answer review questions following each Section, with an answer table provided, strengthen the reader's detailed grasp of the material contained in the Section problems associated with each Section provide practice in applying the principles discussed, and in some cases extend the scope of that material an online separate solutions manual is available for course tutors. The various features of this textbook make it possible for engineering students to become well versed in the 'machinery' of probability theory. They also make the book a useful resource for self-study by practicing engineers and researchers who need a more thorough grasp of particular topics.
Publication Date: 2010-12-20
Statistics for Engineers by Jim MorrisonThis practical text is an essential source of information for those wanting to know how to deal with the variability that exists in every engineering situation. Using typical engineering data, it presents the basic statistical methods that are relevant, in simple numerical terms. In addition, statistical terminology is translated into basic English. In the past, a lack of communication between engineers and statisticians, coupled with poor practical skills in quality management and statistical engineering, was damaging to products and to the economy. The disastrous consequence of setting tight tolerances without regard to the statistical aspect of process data is demonstrated. This book offers a solution, bridging the gap between statistical science and engineering technology to ensure that the engineers of today are better equipped to serve the manufacturing industry. Inside, you will find coverage on: the nature of variability, describing the use of formulae to pin down sources of variation; engineering design, research and development, demonstrating the methods that help prevent costly mistakes in the early stages of a new product; production, discussing the use of control charts, and; management and training, including directing and controlling the quality function. The Engineering section of the index identifies the role of engineering technology in the service of industrial quality management. The Statistics section identifies points in the text where statistical terminology is used in an explanatory context. Engineers working on the design and manufacturing of new products find this book invaluable as it develops a statistical method by which they can anticipate and resolve quality problems before launching into production. This book appeals to students in all areas of engineering and also managers concerned with the quality of manufactured products. Academic engineers can use this text to teach their students basic practical skills in quality management and statistical engineering, without getting involved in the complex mathematical theory of probability on which statistical science is dependent.
Publication Date: 2009-07-20
Random Phenomena by Babatunde A. OgunnaikeMany of the problems that engineers face involve randomly varying phenomena of one sort or another. However, if characterized properly, even such randomness and the resulting uncertainty are subject to rigorous mathematical analysis. Taking into account the uniquely multidisciplinary demands of 21st-century science and engineering, Random Phenomena: Fundamentals of Probability and Statistics for Engineersprovides students with a working knowledge of how to solve engineering problems that involve randomly varying phenomena. Basing his approach on the principle of theoretical foundations before application, Dr. Ogunnaike presents a classroom-tested course of study that explains how to master and use probability and statistics appropriately to deal with uncertainty in standard problems and those that are new and unfamiliar. Giving students the tools and confidence to formulate practical solutions to problems, this book offers many useful features, including: Unique case studies to illustrate the fundamentals and applications of probability and foster understanding of the random variable and its distribution Examples of development, selection, and analysis of probability models for specific random variables Presentation of core concepts and ideas behind statistics and design of experiments Selected "special topics," including reliability and life testing, quality assurance and control, and multivariate analysis As classic scientific boundaries continue to be restructured, the use of engineering is spilling over into more non-traditional areas, ranging from molecular biology to finance. This book emphasizes fundamentals and a "first principles" approach to deal with this evolution. It illustrates theory with practical examples and case studies, equipping readers to deal with a wide range of problems beyond those in the book. About the Author: Professor Ogunnaike is Interim Dean of Engineering at the University of Delaware. He is the recipient of the 2008 American Automatic Control Council's Control Engineering Practice Award, the ISA's Donald P. Eckman Education Award, the Slocomb Excellence in Teaching Award, and was elected into the US National Academy of Engineering in 2012.
Publication Date: 2009-09-21
Introductory Statistics for Engineering Experimentation by Peter R. Nelson; Karen A. F. Copeland; Marie CoffinThe Accreditation Board for Engineering and Technology (ABET) introduced a criterion starting with their 1992-1993 site visits that "Students must demonstrate a knowledge of the application of statistics to engineering problems." Since most engineering curricula are filled with requirements in their own discipline, they generally do not have time for a traditional two semesters of probability and statistics. Attempts to condense that material into a single semester often results in so much time being spent on probability that the statistics useful for designing and analyzing engineering/scientific experiments is never covered. In developing a one-semester course whose purpose was to introduce engineering/scientific students to the most useful statistical methods, this book was created to satisfy those needs. Provides the statistical design and analysis of engineering experiments & problems Presents a student-friendly approach through providing statistical models for advanced learning techniques Covers essential and useful statistical methods used by engineers and scientists
Publication Date: 2003-08-14
Fundamentals of Applied Probability and Random Processes by Oliver C. IbeThis book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book's clear writing style and homework problems make it ideal for the classroom or for self-study. * Good and solid introduction to probability theory and stochastic processes * Logically organized; writing is presented in a clear manner * Choice of topics is comprehensive within the area of probability * Ample homework problems are organized into chapter sections
Publication Date: 2005-10-19
Fundamentals of Probability and Statistics for Engineers by T. T. SoongThis 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.