Katalog książek anglojęzycznych

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1 Katalog książek anglojęzycznych statystyka dla inżynierów Amerykańskie Towarzystwo Statystyczne ogłosiło rok 2013 Międzynarodowym Rokiem Statystyki. Ogólnoświatowa akcja ma na celu uczczenie i docenienie osiągnięć nauk statystycznych. Przyłączyliśmy się do akcji promując najważniejsze książki z tej dziedziny. Przeglądaj katalog z nowościami i najciekawszymi publikacjami. Dowiedz się więcej na

2 Statystyka dla inżynierów Applications of Statistics and Probability in Civil Engineering Michael Faber Taylor & Francis Applied Statistics and Probability for Engineers ,00 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) ,99 Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions. Applied Statistics and Probability for Engineers Bayesian Logical Data Analysis for the Physical Sciences Phil C. Gregory Cambridge University Press ,50 Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions ,99 Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Design and Analysis of Experiments 8E Montgomery Engineering Statistics ,00 The eighth edition of this best selling text continues to help senior under graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyse experiments for improving the quality, efficiency and performance of working systems. The eighth edition of Design and Analysis of Experiments maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book. Continuing to place a strong focus on the use of the computer, this edition includes software examples taken from the four most dominant programs in the field: Design- Expert, Minitab, JMP, and SAS ,99 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. 2

3 Statystyka dla inżynierów Engineering Statistics: Student Solutions Manual Essentials of Probabilty & Statistics for Engineers & Scientists Ronald E. Walpole Pearson Education ,95 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 ,99 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. Methods and Applications of Statistics in Engineering, Quality Control, and the Physical N. Balakrishnan Miller and Freund's Probability and Statistics for Engineers Richard A. Johnson Pearson Education ,00 Inspired by the Encyclopedia of Statistical Sciences, Second Edition (ESS2e), this volume presents a concise, well-rounded focus on the statistical concepts and applications that are essential for understanding gathered data in the fields of engineering, quality control, and the physical sciences. The book successfully upholds the goals of ESS2e by combining both previously-published and newly developed contributions written by over 100 leading academics, researchers, and practitioner in a comprehensive, approachable format. The result is a succinct reference that unveils modern, cutting-edge approaches to acquiring and analyzing data across diverse subject areas within these three disciplines, including operations research, chemistry, physics, the earth sciences,electrical engineering, and quality assurance. In addition, techniques related to survey methodology, computational statistics, and operations research are discussed, where applicable. Topics of coverage include: optimal and stochastic control, artificial intelligence, quantum mechanics, and fractals ,99 This text is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data have been collected from the author's own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the book emphasizes designed experiments, especially twolevel factorial design. Probability and Statistics for Engineers and Scientists Ronald E. Walpole Pearson Education Probability, Statistics, and Reliability for Engineers and Scientists Bilal M. Ayyub Taylor & Francis ,99 This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance of 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 ,99 In a technological society, virtually every engineer and scientist needs to be able to collect, analyze, interpret, and properly use vast arrays of data. This means acquiring a solid foundation in the methods of data analysis and synthesis. Understanding the theoretical aspects is important, but learning to properly apply the theory to real-world problems is essential. Probability, Statistics, and Reliability for Engineers and Scientists, Third Edition introduces the fundamentals of probability, statistics, reliability, and risk methods to engineers and scientists for the purposes of data and uncertainty analysis and modeling in support of decision making. The third edition of this bestselling text presents probability, statistics, reliability, and risk methods with an ideal balance of theory and applications. Clearly written and firmly focused on the practical use of these methods, it places increased emphasis on simulation, particularly as a modeling tool, applying it progressively with projects that continue in each chapter. This provides a measure of continuity and shows the broad use of simulation as a computational tool to inform decision making processes. 3

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