a modern introduction to probability and statistics understanding why and how springer texts in statistics

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A Modern Introduction To Probability And Statistics

Author : F.M. Dekking
ISBN : 9781846281686
Genre : Mathematics
File Size : 22. 96 MB
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Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

Impurity Scattering In Metallic Alloys

Author : Joginder Singh Galsin
ISBN : 0306465744
Genre : Science
File Size : 59. 24 MB
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Theoretical understanding of electronic properties of metallic alloys is of great importance from both fundamental and technological points of view. All the chapters in this book are developed from the fundamentals and are coherently interrelated in a meticulous manner. The book gives a brief account of the crystal structure of both the pure metals and metals with impurities. Physical effects produced by impurities in metals are described in detail. The electronic structure of pure simple and transition metals is described with special reference to rare-earth metals.

Computer Simulation In Physics And Engineering

Author : Martin Oliver Steinhauser
ISBN : 9783110256062
Genre : Science
File Size : 58. 36 MB
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This work is a needed reference for widely used techniques and methods of computer simulation in physics and other disciplines, such as materials science. The work conveys both: the theoretical foundations of computer simulation as well as applications and "tricks of the trade", that often are scattered across various papers. Thus it will meet a need and fill a gap for every scientist who needs computer simulations for his/her task at hand. In addition to being a reference, case studies and exercises for use as course reading are included.

Structural Dynamics Volume 3

Author : Tom Proulx
ISBN : 1441998349
Genre : Technology & Engineering
File Size : 53. 50 MB
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This the fifth volume of five from the 28th IMAC on Structural Dynamics and Renewable Energy, 2010,, brings together 146 chapters on Structural Dynamics. It presents early findings from experimental and computational investigations of on a wide range of area within Structural Dynamics, including studies such as Simulation and Validation of ODS Measurements made Using a Continuous SLDV Method on a Beam Excited by a Pseudo Random Signal, Comparison of Image Based, Laser, and Accelerometer Measurements, Modal Parameter Estimation Using Acoustic Modal Analysis, Mitigation of Vortex-induced Vibrations in Long-span Bridges, and Vibration and Acoustic Analysis of Brake Pads for Quality Control.

Probability Via Expectation

Author : Peter Whittle
ISBN : 0387989552
Genre : Mathematics
File Size : 66. 45 MB
Format : PDF
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This book has exerted a continuing appeal since its original publication in 1970. It develops the theory of probability from axioms on the expectation functional rather than on probability measure, demonstrates that the standard theory unrolls more naturally and economically this way, and that applications of real interest can be addressed almost immediately. New to this edition are chapters giving an economical introduction to dynamic programming, which is then applied to the allocation problems represented by portfolio selection and the multi-armed bandit. The investment theme is continued with a critical investigation of the concept of risk-free trading and the associated Black-Sholes formula, while another new chapter develops the basic ideas of large deviations.

Amstat News

Author :
ISBN : UOM:39015059084387
Genre : Statistics
File Size : 78. 23 MB
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Introduction To Probability And Statistics For Engineers

Author : Milan Holický
ISBN : 9783642383007
Genre : Mathematics
File Size : 70. 55 MB
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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.

Probability With Applications In Engineering Science And Technology

Author : Matthew A. Carlton
ISBN : 9783319524016
Genre : Mathematics
File Size : 27. 48 MB
Format : PDF, Docs
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This updated and revised first-course textbook in applied probability provides a contemporary and lively post-calculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a year-long course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A one-term course would cover material in the core chapters (1-4), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch. 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8 – available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a one-term class on random signals and noise). For a year-long course, core chapters (1-4) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a self-contained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations.

Probability For Statistics And Machine Learning

Author : Anirban DasGupta
ISBN : 1441996346
Genre : Mathematics
File Size : 66. 85 MB
Format : PDF, ePub, Mobi
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This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine learning. It is written in an extremely accessible style, with elaborate motivating discussions and numerous worked out examples and exercises. The book has 20 chapters on a wide range of topics, 423 worked out examples, and 808 exercises. It is unique in its unification of probability and statistics, its coverage and its superb exercise sets, detailed bibliography, and in its substantive treatment of many topics of current importance. This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.

Modern Multivariate Statistical Techniques

Author : Alan J. Izenman
ISBN : 0387781897
Genre : Mathematics
File Size : 42. 76 MB
Format : PDF, ePub
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This is the first book on multivariate analysis to look at large data sets which describes the state of the art in analyzing such data. Material such as database management systems is included that has never appeared in statistics books before.

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