# krainaksiazek statistics and analysis of scientific data 20116043

- znaleziono 51 produktów w 7 sklepach

### Statistics and Analysis of Scientific Data Springer, Berlin

**Książki / Literatura obcojęzyczna**

The revised second edition of this textbook provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. It covers a broad range of numerical and analytical methods that are essential for the correct analysis of scientific data, including probability theory, distribution functions of statistics, fits to two-dimensional data and parameter estimation, Monte Carlo methods and Markov chains.§§Features new to this edition include:§§- a discussion of statistical techniques employed in business science, such as multiple regression analysis of multivariate datasets.§- a new chapter on the various measures of the mean including logarithmic averages.§- new chapters on systematic errors and intrinsic scatter, and on the fitting of data with bivariate errors.§- a new case study and additional worked examples.§- mathematical derivations and theoretical background material have been appropriately marked, to improve the readability of the text.§- end-of-chapter summary boxes, for easy reference.§§As in the first edition, the main pedagogical method is a theory-then-application approach, where emphasis is placed first on a sound understanding of the underlying theory of a topic, which becomes the basis for an efficient and practical application of the material. The level is appropriate for undergraduates and beginning graduate students, and as a reference for the experienced researcher. Basic calculus is used in some of the derivations, and no previous background in probability and statistics is required. The book includes many numerical tables of data, as well as exercises and examples to aid the readers' understanding of the topic.§

Sklep: Libristo.pl

### Statistics And Analysis Of Scientific Data

**Książki Obcojęzyczne>Angielskie>Mathematics & science>Physics>Statistical physicsKsiążki Obcojęzyczne>Angielskie>Technology, enginee...**

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Sklep: Gigant.pl

### Introduction to Statistics and Data Analysis Springer, Berlin

**Książki / Literatura obcojęzyczna**

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. Issues such as judging the credibility of data, analyzing the data, evaluating the reliability of the obtained results and finally drawing the correct and appropriate conclusions from the results are vital. The text is primarily intended for undergraduate students in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R as well as supplementary material that will enable the reader to quickly adapt all methods to their own applications.

Sklep: Libristo.pl

### Scientific Data Analysis

**Książki Obcojęzyczne>Angielskie>Reference, information & interdisciplinary sub.>Research & information: general>Data analysis: generalKsią...**

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Sklep: Gigant.pl

### Statistics and Scientific Method Oxford University Press

**Książki / Literatura obcojęzyczna**

Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended audience of non-mathematically inclined undergraduate or postgraduate students, typically in a single discipline; hence, "statistics for biologists", "statistics for psychologists", and so on. An antidote to technique-oriented service courses, this book is different. It studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, the text aims to give the reader a clear understanding of how core statistical ideas of experimental design, modelling and data analysis are integral to the scientific method. Aimed primarily at beginning postgraduate students across a range of scientific disciplines (albeit with a bias towards the biological, environmental and health sciences), it therefore assumes some maturity of understanding of scientific method, but does not require any prior knowledge of statistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation. Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice, R, whilst the book's web-page includes downloadable data and R code that enables the reader to reproduce all of the analyses in the book and, with easy modifications, to adapt the code to analyse their own data if they wish. However, the book is not intended to be a textbook on statistical computing, and all of the material in the book can be understood without using either R or any other computer software.

Sklep: Libristo.pl

### Statistics for Spatio-Temporal Data Wiley & Sons

**Książki / Literatura obcojęzyczna**

A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods§From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models.§Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes.§Topics of coverage include:§Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs§Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes§Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation§Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data§Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods§From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models.§The authors supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include:§Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs§Spatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes§Development of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation§Quantifying and exploiting spatio-temporal variability in scientific applications, including case studies based on real-world environmental data§Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material.§Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Sklep: Libristo.pl

### Data-Driven Modeling & Scientific Computation Oxford University Press

**Książki / Literatura obcojęzyczna**

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: * statistics, * time-frequency analysis, and * low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be used in combination to give critical insight into the fundamental workings of various problems. Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences. An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Sklep: Libristo.pl

### Data-Driven Modeling & Scientific Computation Oxford University Press

**Książki / Literatura obcojęzyczna**

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science. The enormous data sets now routinely encountered in the sciences provide an incentive to develop mathematical techniques and computational algorithms that help synthesize, interpret and give meaning to the data in the context of its scientific setting. A specific aim of this book is to integrate standard scientific computing methods with data analysis. By doing so, it brings together, in a self-consistent fashion, the key ideas from: * statistics, * time-frequency analysis, and * low-dimensional reductions The blend of these ideas provides meaningful insight into the data sets one is faced with in every scientific subject today, including those generated from complex dynamical systems. This is a particularly exciting field and much of the final part of the book is driven by intuitive examples from it, showing how the three areas can be used in combination to give critical insight into the fundamental workings of various problems. Data-Driven Modeling and Scientific Computation is a survey of practical numerical solution techniques for ordinary and partial differential equations as well as algorithms for data manipulation and analysis. Emphasis is on the implementation of numerical schemes to practical problems in the engineering, biological and physical sciences. An accessible introductory-to-advanced text, this book fully integrates MATLAB and its versatile and high-level programming functionality, while bringing together computational and data skills for both undergraduate and graduate students in scientific computing.

Sklep: Libristo.pl

### Statistics for Spatial Data John Wiley & Sons Inc

**Książki / Literatura obcojęzyczna**

The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics -- analyzing spatial data through statistical models -- has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.

Sklep: Libristo.pl

### Functional and Shape Data Analysis Springer, Berlin

**Książki / Literatura obcojęzyczna**

This textbook for courses on function data analysis and shape data analysis describes how to define, compare, and mathematically represent shapes, with a focus on statistical modeling and inference. It is aimed at graduate students in analysis in statistics, engineering, applied mathematics, neuroscience, biology, bioinformatics, and other related areas. The interdisciplinary nature of the broad range of ideas covered-from introductory theory to algorithmic implementations and some statistical case studies-is meant to familiarize graduate students with an array of tools that are relevant in developing computational solutions for shape and related analyses. These tools, gleaned from geometry, algebra, statistics, and computational science, are traditionally scattered across different courses, departments, and disciplines; Functional and Shape Data Analysis offers a unified, comprehensive solution by integrating the registration problem into shape analysis, better preparing graduate students for handling future scientific challenges.§§Recently, a data-driven and application-oriented focus on shape analysis has been trending. This text offers a self-contained treatment of this new generation of methods in shape analysis of curves. Its main focus is shape analysis of functions and curves-in one, two, and higher dimensions-both closed and open. It develops elegant Riemannian frameworks that provide both quantification of shape differences and registration of curves at the same time. Additionally, these methods are used for statistically summarizing given curve data, performing dimension reduction, and modeling observed variability. It is recommended that the reader have a background in calculus, linear algebra, numerical analysis, and computation.§

Sklep: Libristo.pl

### Data Mining and Analysis Cambridge University Press

**Książki / Literatura obcojęzyczna**

The fundamental algorithms in data mining and analysis form the basis for the emerging field of data science, which includes automated methods to analyze patterns and models for all kinds of data, with applications ranging from scientific discovery to business intelligence and analytics. This textbook for senior undergraduate and graduate data mining courses provides a broad yet in-depth overview of data mining, integrating related concepts from machine learning and statistics. The main parts of the book include exploratory data analysis, pattern mining, clustering, and classification. The book lays the basic foundations of these tasks, and also covers cutting-edge topics such as kernel methods, high-dimensional data analysis, and complex graphs and networks. With its comprehensive coverage, algorithmic perspective, and wealth of examples, this book offers solid guidance in data mining for students, researchers, and practitioners alike. Key features:

Sklep: Libristo.pl

### Bayesian Ideas and Data Analysis ROUTLEDGE

**Książki / Literatura obcojęzyczna**

Emphasizing the use of WinBUGS and R to analyze real data, thsi book presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data.

Sklep: Libristo.pl

### Introduction to Data Analysis and Graphical Presentation in Biostatistics with R, 1 Springer, Berlin

**Książki / Literatura obcojęzyczna**

Through real-world datasets, this book shows the reader how to work with material in biostatistics using the open source software R. These include tools that are critical to dealing with missing data, which is a pressing scientific issue for those engaged in biostatistics. Readers will be equipped to run analyses and make graphical presentations based on the sample dataset and their own data. The hands-on approach will benefit students and ensure the accessibility of this book for readers with a basic understanding of R. §Topics include: an introduction to Biostatistics and R, data exploration, descriptive statistics and measures of central tendency, t-Test for independent samples, t-Test for matched pairs, ANOVA, correlation and linear regression, and advice for future work.§

Sklep: Libristo.pl

### Numeric Computation and Statistical Data Analysis on the Java Platform Springer, Berlin

**Książki / Literatura obcojęzyczna**

Numerical§computation, knowledge discovery and statistical data analysis integrated with§powerful 2D and 3D graphics for visualization are the key topics of this book. The§Python code examples powered by the Java platform can easily be transformed to§other programming languages, such as Java, Groovy, Ruby and BeanShell. This§book equips the reader with a§computational platform which, unlike other statistical programs, is not limited§by a single programming language.§The author§focuses on practical programming aspects and covers a broad range of topics,§from basic introduction to the Python language on the Java platform (Jython),§to descriptive statistics, symbolic calculations, neural networks, non-linear§regression analysis and many other data-mining topics. He discusses how to find§regularities in real-world data, how to classify data, and how to process data§for knowledge discoveries. The code snippets are so short that they easily fit into§single pages.§§Numeric Computation and Statistical Data§Analysis on the Java Platform is a great choice for those who want to learn how statistical§data analysis can be done using popular programming languages, who want to§integrate data analysis algorithms in full-scale applications, and deploy such§calculations on the web pages or computational servers regardless§of their operating system. It is an excellent reference for scientific computations to solve§real-world problems using a comprehensive stack of open-source Java§libraries included in the DataMelt (DMelt) project and will be§appreciated by many data-analysis scientists, engineers and students . §

Sklep: Libristo.pl

### Introduction To Statistical Analysis Of Laboratory Data

**Książki Obcojęzyczne>Angielskie>Mathematics & science>Science: general issues>Scientific equipment, experiments & techniquesKsiążki Obcoję...**

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Sklep: Gigant.pl

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