# krainaksiazek elementary statistical analysis 20107118

- znaleziono 23 produkty w 4 sklepach

### Statistical Physics Dover Publications

**Książki / Literatura obcojęzyczna**

PART I Principles of statistical thermodynamics 1 The first law of thermodynamics 1-1. Systems and state variables 1-2. The equation of state 1-3. "Large" and "small" systems; statistics of Gibbs versus Boltzman" 1-4. "The First Law; heat, work, and energy" 1-5. Precise formulation of the First Law for quasistatic change Problems 2 Elementary statistical methods in physics 2-1. Probability distributions; binomial and Poisson distributions 2-2. Distribution function for large numbers; Gaussian distribution 2-3. Statistical dealing with averages in time; virial theorem Problems 3 Statistical counting in mechanics 3-1. Statistical counting in classical mechanics; Liouville theorem and ergodic hypothesis 3-2. Statistical counting in quantum mechanics Problems 4 The Gibbs-Boltzmann distribution law 4-1. Derivation of the Gibbsian or canonical distribution 4-2. Elucidation of the temperature concept 4-3. The perfect gas; Maxwellian distribution 4-4. Energy distribution for small and large samples; thermodynamic limit 4-5. Equipartition theorem and dormant degrees of freedom Problems 5 Statistical justification of the Second Law 5-1. Definition of entropy; entropy and probability 5-2. "Proof of the Second Law for "clamped" systems" 5-3. The Ehrenfest or adiabatic principle 5-4. Extension of the Second Law to general systems 5-5. Simple examples of entropy expressions 5-6. Examples of entropy-increasing processes 5-7. Third Law of thermodynamics Problems 6 Older ways to the Second Law 6-1. Proof by the method of Carnot cycles 6-2. Proof of Caratheodory Problems 7 Thermodynamic exploitation of the Second Law; mass transfer problems 7-1. Legendre transformations and thermodynamic potentials 7-2. Thermodynamics of bulk properties; extensive and intensive variables 7-3. Equilibrium of two phases; equation of Clausius and Clapeyron 7-4. "Equilibrium of multiphase, multicomponents systems; Gibbs' phase rule" 7-5. Refined study of the two-phase equilibrium; vapor pressure of small drops Problems 8 The grand ensemble; classical statistics of independent particles 8-1. Statistics of the grand ensemble 8-2. Other modified statistics; Legendre-transformed partition functions 8-3. Maxwell-Boltzmann particle statistics 8-4. Particle versus system partition function; Gibbs paradox 8-5. Grand ensemble formulas for Boltzmann particles Problems 9 Quantum statistics of independent particles 9-1. Pauli exclusion principle 9-2. Fermi-Dirac statistics 9-3. Theory of the perfect Fermi gas 9-4. Bose-Einstein statistics 9-5. The perfect Bose gas; Einstein condensation PART II Equilibrium statistics of special systems 10 Thermal properties of electromagnetic radiation 10-1. Realization of equilibrium radiation; black body radiation 10-2. Thermodynamics of black body radiation; laws of Stefan-Boltzmann and Wien 10-3. Statistics of black body radiation; Planck's formula Problems 11 Statistics of the perfect molecular gas 11-1. Decomposition of the degrees of freedom of a perfect molecular gas 11-2. Center-of-mass motion of gaseous molecules 11-3. Rotation of gaseous molecules 11-4. The rotational heat capacity of hydrogen 11-5. Vibrational motion of diatomic molecules 11-6. The law of mass action in perfect molecular gases Problems 12 The problem of the imperfect gas 12-1. Equation of state from the partition function 12-2. Equation of state from the virial theorem 12-3. Approximate results from the virial theorem; van der Waals' equation 12-4. The Joule-Thomson effect 12-5. Ursell-Mayer expansion of the partition function; diagram summation 12.6 Mayer's cluster expansion theorem 12-7. Mayer's formulation of the equation of state of imperfect gases 12-8. Phase equilibrium between liquid and gas; critical phenomenon Problems 13 Thermal properties of crystals 13-1. Relation between the vibration spectrum and the heat capacity of solids 13-2. Vibrational bands of crystals; models in one dimension 13-3. Vibrational bands of crystals; general theory 13-4. Debye theory of the heat capacity of solids 13-5. Vapor pressure of solids Problems 14 Statistics of conduction electrons in solids 14-1. The distinction of metals and insulators in fermi statistics 14-2. Semiconductors: electrons and holes 14-3. Theory of thermionic emission 14-4. Degeneracy and non-degeneracy: electronic heat capacity in metals 14-5. "Doped" semiconductors: n-p junctions" Problems 15 Statistics of magnetism 15-1. Paramagnetism of isolated atoms and ions 15-2. Pauli paramagnetism 15-3. Ferromagnetism; internal field model 15-4. Ferromagnetism; Ising model 15-5. Spin wave theory of magnetization Problems 16 Mathematical analysis of the Ising model 16-1. Eigenvalue method for periodic nearest neighbor systems 16-2. One-dimensional Ising model 16-3. Solution of the two-dimensional Ising model by abstract algebra 16-4. Analytic reduction of the results for the two dimensional Ising model 17 Theory of dilute solutions 17-1. Thermodynamic functions for dilute solutions 17-2. Osmotic pressure and other modifictions of solvent properties 17-3. Behavior of solutes in dilute solutions; analogy to perfect gases 17-4. Theory of strong electrolytes Problems "PART III Kinetic theory, transport coefficients and fluctuations" 18 Kinetic justification of equilibrium statistics; Boltzmann transport equation 18-1. Derivation of the Boltmann transport equation 18-2. Equilibrium solutions of the Boltzmann transport equation; Maxwellian distribution 18-3. Boltzmann's H-theorem 18-4. Paradoxes associated with the Boltzmann transport equation; Kac ring model 18-5. Relaxation rate spectrum for Maxwellian molecules 18-6. Formal relaxtion theory of the Boltzmann equation Problems 19 Transport properties of gases 19-1. Elementary theory of transport phenomena in gases 19-2. Determination of transport coefficients from the Boltzmann equation 19-3. Discussion of empirical viscosity data Problems 20 Kinetics of charge carriers in solics and liquids 20-1. Kinetic theory of Ohmic conduction 20-2. Nature of the charge carriers in matter; Nernst relation 20-3. Nature of the electric carriers in metals; law of Wiedmann and Franz 20-4. Separation of carrier density and carrier velocity; Hall effect Problems 21 Kinetics of charge carriers in gases 21-1. Kinetics of the polarization force 21-2. "High field" velocity distribution of ions and electrons in gases" 21-3. Velocity distribution functions for electrons; formulas of Davydov and Druyvesteyn 22 Fluctuations and Brownian motion 22-1. Equilibrium theory of fluctuations 22-2. Brownian motion 22-3. Spectral decompostion of Brownian motion ; Wiener-Khinchin theorem Problems 23 Connection between transport coefficients and equilibrium statistics 23-1. Nyquist relation 23-2. Kubo's equilbrium expression for electrical conductivity 23-3. Reduction of the Kubo relation to those of Nernst and Nyquist 23-4. Onsager relations Problem Supplementary Literature Answers to Problems Index

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### Supermathematics and its Applications in Statistical Physics Springer, Berlin

**Książki / Literatura obcojęzyczna**

This text presents the mathematical concepts of Grassmann§variables and the method of supersymmetry to a broad audience of physicists§interested in applying these tools to disordered and critical systems, as well§as related topics in statistical physics. Based on many courses and seminars§held by the author, one of the pioneers in this field, the reader is given a§systematic and tutorial introduction to the subject matter.§§The algebra and analysis of Grassmann variables is§presented in part I. The mathematics of these variables is applied to a random§matrix model, path integrals for fermions, dimer models and the Ising model in§two dimensions. Supermathematics - the use of commuting and anticommuting§variables on an equal footing - is the subject of part II. The properties of§supervectors and supermatrices, which contain both commuting and Grassmann§components, are treated in great detail, including the derivation of integral§theorems. In part III, supersymmetric physical models are considered. While§supersymmetry was first introduced in elementary particle physics as exact§symmetry between bosons and fermions, the formal introduction of anticommuting§spacetime components, can be extended to problems of statistical physics, and,§since it connects states with equal energies, has also found its way into§quantum mechanics.§§Several models are considered in the applications, after§which the representation of the random matrix model by the nonlinear§sigma-model, the determination of the density of states and the level§correlation are derived. Eventually, the mobility edge behavior is discussed§and a short account of the ten symmetry classes of disorder, two-dimensional§disordered models, and superbosonization is given.§§

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### Elements of Statistical Method (Classic Reprint) Forgotten Books

**Książki / Literatura obcojęzyczna**

Excerpt from The Elements of Statistical Method The purpose of this book is to furnish a simple text in statistical method for the benefit of those students, economists, administrative officials, writers, or other members of the educated public who desire a general knowledge of the more elementary processes involved in the scientific study, analysis, and use of large masses of numerical data. While it is intended primarily for the use of those interested in sociology, political economy, or administration, the general principles set forth are applicable likewise to every variety of statistical data. The author has found that the members of his classes in this subject were not, as a rule, expert mathematicians, and he believes that this is true of a majority of those persons who are called upon to make practical use of statistics, hence, no pretense whatever has been made, in this work, of presenting any but the most simple of the mathematical theorems upon which statistical method is based. So far as the author is aware, there is no book published in America which attempts to cover the field of statistical method in its present state of advancement. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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### Data Analysis Springer, Berlin

**Książki / Literatura obcojęzyczna**

The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The programs (source code, Java classes and documentation) and extensive appendices to the main text are available for free download from the book s page at www.springer.com.§Contents §Probabilities. Random variables. §Random numbers and the Monte Carlo Method. §Statistical distributions (binomial, Gauss, Poisson). Samples. Statistical tests. §Maximum Likelihood. Least Squares. Regression. Minimization. §Analysis of Variance. Time series analysis. §Audience §The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data§in laboratory courses, §in working for bachelor or master degrees, §in thesis work, §in research and professional work. § The book is concise, but gives a sufficiently rigorous mathematical treatment of practical statistical methods for data analysis; it can be of great use to all who are involved with data analysis. Physicalia § Serves as a nice reference guide for any scientist interested in the fundamentals of data analysis on the computer. The American Statistician§ This lively and erudite treatise covers the theory of the main statistical tools and their practical applications a first rate university textbook, and good background material for the practicing physicist. Physics Bulletin§The Author §Siegmund Brandt is Emeritus Professor of Physics at the University of Siegen. With his group he worked on experiments in elementary-particle physics at the research centers DESY in Hamburg and CERN in Geneva in which the analysis of the experimental data plays an important role. He is author or coauthor of textbooks which have appeared in ten languages.§

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### Analysis of Biomarker Data John Wiley & Sons Inc

**Książki / Literatura obcojęzyczna**

A "how to" guide for applying statistical methods to biomarker data analysis§§Presenting a solid foundation for the statistical methods that are used to analyze biomarker data, Analysis of Biomarker Data: A Practical Guide features preferred techniques for biomarker validation. The authors provide descriptions of select elementary statistical methods that are traditionally used to analyze biomarker data with a focus on the proper application of each method, including necessary assumptions, software recommendations, and proper interpretation of computer output. In addition, the book discusses frequently encountered challenges in analyzing biomarker data and how to deal with them, methods for the quality assessment of biomarkers, and biomarker study designs.§§Covering a broad range of statistical methods that have been used to analyze biomarker data in published research studies, Analysis of Biomarker Data: A Practical Guide also features:§A greater emphasis on the application of methods as opposed to the underlying statistical and mathematical theory§The use of SAS(r), R, and other software throughout to illustrate the presented calculations for each example§Numerous exercises based on real-world data as well as solutions to the problems to aid in reader comprehension§The principles of good research study design and the methods for assessing the quality of a newly proposed biomarker§A companion website that includes a software appendix with multiple types of software and complete data sets from the book's examples§Analysis of Biomarker Data: A Practical Guide is an ideal upper-undergraduate and graduate-level textbook for courses in the biological or environmental sciences. An excellent reference for statisticians who routinely analyze and interpret biomarker data, the book is also useful for researchers who wish to perform their own analyses of biomarker data, such as toxicologists, pharmacologists, epidemiologists, environmental and clinical laboratory scientists, and other professionals in the health and environmental sciences.

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### Introduction to Design and Analysis of Experiments Wiley

**Książki / Literatura obcojęzyczna**

Introduction to Design and Analysis of Experiments explains how to choose sound and suitable design structures and engages students in understanding the interpretive and constructive natures of data analysis and experimental design. Cobb's approach allows students to build a deep understanding of statistical concepts over time as they analyze and design experiments. The field of statistics is presented as a matrix, rather than a hierarchy, of related concepts. Developed over years of classroom use, this text can be used as an introduction to statistics emphasizing experimental design or as an elementary graduate survey course. Widely praised for its exceptional range of intelligent and creative exercises, and for its large number of examples and data sets, Introduction to Design and Analysis of Experiments--now offered in a convenient paperback format--helps students increase their understanding of the material as they come to see the connections between diverse statistical concepts that arise from the experiments around which the text is built.

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### Vector Analysis Forgotten Books

**Książki / Literatura obcojęzyczna**

Excerpt from Vector Analysis: A Text-Book for the Use of Students of Mathematics and Physics When I undertook to adapt the lectures of Professor Gibbs on Vector Analysis for publication in the Yale Bicentennial Series, Professor Gibbs himself was already so fully engaged upon his work to appear in the same series, Elementary Principles in Statistical Mechanics, that it was understood no material assistance in the composition of this book could be expected from him. For this reason he wished me to feel entirely free to use my own discretion alike in the selection of the topics to be treated and in the mode of treatment. It has been my endeavor to use the freedom thus granted only in so far as was necessary for presenting his method in text-book form. By far the greater part of the material used in the following pages has been taken from the course of lectures on Vector Analysis delivered annually at the University by Professor Gibbs. Some use, however, has been made of the chapters on Vector Analysis in Mr. Oliver Heaviside's Electromagnetic Theory (Electrician Series, 1893) and in Professor Föppl's lectures on Die Maxwell'sche Theorie der Electricitat (Teubner, 1894). My previous study of Quaternions has also been of great assistance. The material thus obtained has been arranged in the way which seems best suited to easy mastery of the subject. Those Arts, which it seemed best to incorporate in the text but which for various reasons may well be omitted at the first reading have been marked with an asterisk (*). Numerous illustrative examples have been drawn from geometry, mechanics, and physics. Indeed, a large part of the text has to do with applications of the method. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

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### Introduction to Error Analysis PALGRAVE MACMILLAN

**Książki / Literatura obcojęzyczna**

The need for error analysis is captured in the book's arresting cover shot - of the 1895 Paris train disaster (also available as a wall poster). The early chapters teach elementary techniques of error propagation and statistical analysis to enable students to produce successful lab reports. Later chapters treat a number of more advanced mathematical topics, with many examples from mechanics and optics. End-of-chapter problems include many that call for use of calculators or computers, and numerous figures help readers visualize uncertainties using error bars. "Score a hit! ...the book reveals the exceptional skill of the author as lecturer and teacher...a valuable reference work for any student (or instructor) in the sciences and engineering." The Physics Teacher "This is a well written book with good illustrations, index and general bibliography...The book is well suited for engineering and science courses at universities and as a basic reference text for those engineers and scientists in practice." Strain, Journal of the British Society for Strain Measurement

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### Modern Applied Biostatistical Methods Using S-Plus Oxford University Press

**Zdrowie, medycyna**

Statistical analysis typically involves applying theoretically generated techniques to the description and interpretation of collected data. In this text, theory, application and interpretation are combined to present the entire biostatistical process for a series of elementary and intermediate analytic methods. The theoretical basis for each method is discussed with a minimum of mathematics and is applied to a research data example using a computer system called S-PLUS. This system produces concrete numerical results and increases one's understanding of the fundamental concepts and methodology of statistical analysis.;This text is not a computer manual, even though it makes extensive use of computer language to describe and illustrate applied statistical techniques. This makes the details of the statistical process readily accessible, providing insight into how and why a statistical method identifies the properties of sampled data. The first chapter gives a simple overview of the S-PLUS language. The subsequent chapters use this valuable statistical tool to present a variety of analytic approaches.;Combining statistical logic, data and computer tools, the author explores such topics as random number generation, general linear models, estimation, analysis of tabular data, analysis of variance and survival analysis. The end result is a clear and complete explanation of the way statistical methods can help one gain an understanding of collected data.;Modern Applied Biostatistical Methods is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis.

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### Modern Applied Biostatistical Methods Using S-Plus Oxford University Press

**Medycyna > English Division**

Statistical analysis typically involves applying theoretically generated techniques to the description and interpretation of collected data. In this text, theory, application and interpretation are combined to present the entire biostatistical process for a series of elementary and intermediate analytic methods. The theoretical basis for each method is discussed with a minimum of mathematics and is applied to a research data example using a computer system called S-PLUS. This system produces concrete numerical results and increases one's understanding of the fundamental concepts and methodology of statistical analysis. This text is not a computer manual, even though it makes extensive use of computer language to describe and illustrate applied statistical techniques. This makes the details of the statistical process readily accessible, providing insight into how and why a statistical method identifies the properties of sampled data. The first chapter gives a simple overview of the S-PLUS language. The subsequent chapters use this valuable statistical tool to present a variety of analytic approaches. Combining statistical logic, data and computer tools, the author explores such topics as random number generation, general linear models, estimation, analysis of tabular data, analysis of variance and survival analysis. The end result is a clear and complete explanation of the way statistical methods can help one gain an understanding of collected data. Modern Applied Biostatistical Methods is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis.

Sklep: Ksiazki-medyczne.eu

### Statistics John Wiley & Sons Inc

**Książki / Literatura obcojęzyczna**

"...I know of no better book of its kind..." (Journal of the Royal Statistical Society, Vol 169 (1), January 2006)§§A revised and updated edition of this bestselling introductory textbook to statistical analysis using the leading free software package R§§This new edition of a bestselling title offers a concise introduction to a broad array of statistical methods, at a level that is elementary enough to appeal to a wide range of disciplines. Step-by-step instructions help the non-statistician to fully understand the methodology. The book covers the full range of statistical techniques likely to be needed to analyse the data from research projects, including elementary material like t--tests and chi--squared tests, intermediate methods like regression and analysis of variance, and more advanced techniques like generalized linear modelling.§§Includes numerous worked examples and exercises within each chapter.

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### Compendium of Theoretical Physics Springer, Berlin

**Książki / Literatura obcojęzyczna**

The Compendium of Theoretical Physics contains the canonical curriculum of theoretical physics. From classical mechanics over electrodynamics, quantum mechanics and statistical physics/thermodynamics, all topics are treated axiomatic-deductively and confimed by exercises, solutions and short summaries.Mechanics, Electrodynamics, Quantum Mechanics, and Statistical Mechanics and Thermodynamics comprise the canonical undergraduate curriculum of theoretical physics. In Compendium of Theoretical Physics, Armin Wachter and Henning Hoeber offer a concise, rigorous and structured overview that will be invaluable for students preparing for their qualifying examinations, readers needing a supplement to standard textbooks, and research or industrial physicists seeking a bridge between extensive textbooks and formula books.§The authors take an axiomatic-deductive approach to each topic, starting the discussion of each theory with its fundamental equations. By subsequently deriving the various physical relationships and laws in logical rather than chronological order, and by using a consistent presentation and notation throughout, they emphasize the connections between the individual theories. The reader s understanding is then reinforced with exercises, solutions and topic summaries.§Unique Features:§Every topic is reviewed axiomatically-deductively and then reinforced through exercises, solutions and summaries§Each subchapter ends with a set of applications, making the Compendium an ideal review of theoretical physics for physicists working in industry or research§A Mathematical Appendix covers vector operations, integral theorems, partial differential quotients, complete function systems, Fourier analysis, Bessel functions, spherical Bessel functions, Legendre functions, Legendre polynomials and spherical harmonics§Armin Wachter holds a Ph.D. in Physics from the John von Neumann Institute for Computing (NIC) / Research Centre of Jülich, Germany. His research interests include theoretical elementary particle physics, heavy quark physics, heavy meson spectroscopy, algorithms on parallel computers, and lattice gauge theory. He is presently writing a textbook on relativistic quantum mechanics for Springer.§Henning Hoeber received his Ph.D. in Physics from the University of Edinburgh, Scotland and has since held research positions at the John von Neumann Institute for Computing (NIC) / Research Centre of Jülich, Germany and the University of Wuppertal, Germany. His research interests include elementary particle physics, lattice gauge theory, and computational physics, and since 1998 he has done extensive work in the fields of seismic processing, time series analysis, statistical and transform methods for seismic signal processing, and elastic wave propagation.

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### Applied Probability Springer, Berlin

**Książki / Literatura obcojęzyczna**

This textbook on applied probability is intended for graduate students in applied mathematics, biostatistics, computational biology, computer science, physics, and statistics. It presupposes knowledge of multivariate calculus, linear algebra, ordinary differential equations, and elementary probability theory. Given these prerequisites, Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences. Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapters 6 through 11 present core material on stochastic processes. If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material here for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes. Finally, Chapters 12 and 13 develop the Chen-Stein method of Poisson approximation and connections between probability and number theory. Kenneth Lange is Professor of Biomathematics and Human Genetics and Chair of the Department of Human Genetics at the UCLA School of Medicine. He has held appointments at the University of New Hampshire, MIT, Harvard, and the University of Michigan. While at the University of Michigan, he was the Pharmacia & Upjohn Foundation Professor of Biostatistics.This textbook on applied probability is intended for graduate students in applied mathematics, biostatistics, computational biology, computer science, physics, and statistics. It presupposes knowledge of multivariate calculus, linear algebra, ordinary differential equations, and elementary probability theory. Given these prerequisites, Applied Probability presents a unique blend of theory and applications, with special emphasis on mathematical modeling, computational techniques, and examples from the biological sciences.§Chapter 1 reviews elementary probability and provides a brief survey of relevant results from measure theory. Chapter 2 is an extended essay on calculating expectations. Chapter 3 deals with probabilistic applications of convexity, inequalities, and optimization theory. Chapters 4 and 5 touch on combinatorics and combinatorial optimization. Chapters 6 through 11 present core material on stochastic processes. If supplemented with appropriate sections from Chapters 1 and 2, there is sufficient material here for a traditional semester-long course in stochastic processes covering the basics of Poisson processes, Markov chains, branching processes, martingales, and diffusion processes. Finally, Chapters 12 and 13 develop the Chen-Stein method of Poisson approximation and connections between probability and number theory.§Kenneth Lange is Professor of Biomathematics and Human Genetics and§Chair of the Department of Human Genetics at the UCLA School of Medicine. He has held appointments at the University of New Hampshire, MIT, Harvard, and the University of Michigan. While at the University of Michigan, he was the Pharmacia & Upjohn Foundation Professor of Biostatistics. His research interests include human genetics, population modeling, biomedical imaging, computational statistics,§and applied stochastic processes. Springer-Verlag published his books§Numerical Analysis for Statisticians and Mathematical and Statistical Methods for Genetic Analysis Second Edition, in 1999 and 2002, respectively.

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### Probabilistic Modeling in Bioinformatics and Medical Informatics Springer, Berlin

**Książki / Literatura obcojęzyczna**

Probabilistic Modelling in Bioinformatics and Medical Informatics has been written for researchers and students in statistics, machine learning, and the biological sciences. The first part of this book provides a self-contained introduction to the methodology of Bayesian networks. The following parts demonstrate how these methods are applied in bioinformatics and medical informatics. All three fields - the methodology of probabilistic modeling, bioinformatics, and medical informatics - are evolving very quickly. The text should therefore be seen as an introduction, offering both elementary tutorials as well as more advanced applications and case studies. TOC:From the Contents. A Leisurely Look at Statistical Inference. Introduction to Learning Bayesian Networks from Data. A Casual View of Multi-Layer Perceptrons as Probability Models.- Introduction to Statistical Phylogenetics. Detecting Recombination in DNA Sequence Alignments. RNA-Based Phylogenetic Methods. Statistical Methods in Microarray Gene Expression Data Analysis. Inferring Genetic Regulatory Networks from Microarray Experiments with Bayesian Networks. Modelling Genetic Regulatory Networks using Gene Expression Profiling and State Space Models.- An Anthology of Probabilistic Models for Medical Informatics. Bayesian Analysis of Population Pharmacokinetic/Pharmacodynamic Models. Assessing the Effectiveness of Bayesian Feature Selection. Bayes Consistent Classification of EEG Data by Approximate Marginalisation. Ensemble Hidden Markov Models with Extended Observation Densities for Biosignal Analysis. A Probabilistic Network for Fusion of Data and Knowledge in Clinical Microbiology. Software for Probability Models in Medical Informatics.

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### MATLAB Statistics Springer, Berlin

**Książki / Literatura obcojęzyczna**

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.§§MATLAB Statistics introduces you to MATLAB and begins by showing you how to use the Basic Module of MATLAB statistical functions, from the elementary mathematical functions, to special mathematical functions and the functions you can use in MATLAB to perform data analysis and basic statistical analysis.§§You're then introduced to the MATLAB Statistics Toolbox, which extends the basic statistical functions of MATLAB, and you'll find practical hands-on examples throughout the book on how to use these extended MATLAB functions for descriptive statistics, probabilistic models, discrete and continuous random variables, confidence intervals and hypothesis contrasts, models of linear and non-linear regression, multivariate data analysis, quality control, design of experimentation and other content of industrial statistics.§§

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t1=0.052, t2=0, t3=0, t4=0.027, t=0.052