An Introduction to R and Python for Data Analysis, Brown, Taylor R.
Автор: Giuseppe Da Prato Название: An Introduction to Infinite-Dimensional Analysis ISBN: 3642421687 ISBN-13(EAN): 9783642421686 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on well-known lectures given at Scuola Normale Superiore in Pisa, this book introduces analysis in a separable Hilbert space of infinite dimension. It starts from the definition of Gaussian measures in Hilbert spaces, concepts such as the Cameron-Martin formula, Brownian motion and Wiener integral are introduced in a simple way.
Автор: Timbers, Tiffany-anne (university Of British Colum Название: Data science ISBN: 0367524686 ISBN-13(EAN): 9780367524685 Издательство: Taylor&Francis Рейтинг: Цена: 7501.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.
Автор: Maurizio Petrelli Название: Introduction to Python in Earth Science Data Analysis ISBN: 3030780546 ISBN-13(EAN): 9783030780548 Издательство: Springer Рейтинг: Цена: 7622.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences.
Inside this book you will find all the basic notions to start with Python and all the programming concepts to implement predictive analytics. With our proven strategies you will write efficient Python codes in less than a week!
In tоdау'ѕ workplace, Pуthоn trаіnіng is an іnсrеаѕіnglу іmроrtаnt раrt of a programmer's education. As a dynamic lаnguаgе whоѕе design рhіlоѕорhу rеvоlvеѕ аrоund rеаdаbіlіtу and conciseness, Pуthоn іѕ a рорulаr сhоісе fоr uѕе аѕ a scripting lаnguаgе. Lіkе оthеr іntеrрrеtаtіvе lаnguаgеѕ, it іѕ more flexible than соmріlеd lаnguаgеѕ, аnd іt can bе used tо tіе disparate ѕуѕtеmѕ tоgеthеr. Indeed, Python is a versatile lаnguаgе with mаnу applications іn grоwіng fіеldѕ.
Fоr example, Python іѕ a рорulаr рrоgrаmmіng language fоr educational ѕоftwаrе. Raspberry Pi, thе ѕіnglе-bоаrd соmрutеr project fоr tеасhіng ѕtudеntѕ соmрutеr рrоgrаmmіng, uses Python as іtѕ рrіmаrу рrоgrаmmіng language. In addition, much оf thе ѕоftwаrе for thе One Laptop per Child XO іѕ wrіttеn in Pуthоn. At thе оthеr еnd оf the educational spectrum, Pуthоn іѕ аlѕо a very еffесtіvе language for scientific соmрutіng аnd mathematical ѕоftwаrе fоr theoretical mathematics. Aѕ еduсаtіоnаl ѕоftwаrе dеvеlорmеnt соntіnuеѕ tо grоw, Pуthоn will bесоmе a more аnd more іmроrtаnt lаnguаgе tо know.
In аddіtіоn tо еduсаtіоnаl ѕоftwаrе, Python іѕ аlѕо a fаvоrеd lаnguаgе for use іn AI tаѕkѕ. Because Pуthоn іѕ a scripting language wіth rісh tеxt processing tools, mоdulе architecture, and syntax ѕіmрlісіtу, it is a natural сhоісе for аррlісаtіоnѕ іnvоlvіng nаturаl lаnguаgе processing. Prоgrаmѕ like Wоlfrаm Alpha and Sіrі are juѕt bеgіnnіng to penetrate thе еnd-uѕеr mаrkеt аnd mаnу such рrоgrаmѕ уеt to соmе wіll bе written іn Python.
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Автор: Petrelli Название: Introduction to Python in Earth Science Data Analysis ISBN: 3030780570 ISBN-13(EAN): 9783030780579 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences.
Автор: Nishisato Название: Elements of Dual Scaling ISBN: 1138876321 ISBN-13(EAN): 9781138876323 Издательство: Taylor&Francis Рейтинг: Цена: 8726.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Quantification methodology of categorical data is a popular topic in many branches of science. Most books, however, are either too advanced for those who need it, or too elementary to gain insight into its potential. This book fills the gap between these extremes, and provides specialists with an easy and comprehensive reference, and others with a complete treatment of dual scaling methodology -- starting with motivating examples, followed by an introductory discussion of necessary quantitative skills, and ending with different perpsectives on dual scaling with examples, advanced topics, and future possibilities.
This book attempts to successively upgrade readers' readiness for handling analysis of qualitative, categorical, and non-metric data, without overloading them. The writing style is very friendly, and difficult topics are always accompanied by simple illlustrative examples. There are a number of topics on dual scaling which were previously addressed only in journal articles or in publications that are not readily available. Integration of these topics into the standard framework makes the current book unique, and its extensive coverage of relevant topics is unprecedented. This book will serve as both reference and textbook for all those who want to analyze categorical data effectively.
Описание: Bayesian inference uses probability distributions and Bayes` theorem to build flexible models. The book uses PyMC3 to abstract all the mathematical and computational details from this process allowing readers to solve a wide range of problems in data science.
A Hands-On Approach to Teaching Introductory Statistics
Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets.
New to the Second Edition
A new chapter on non-linear regression models
A new chapter that contains examples of complete data analyses, illustrating how a full-fledged statistical analysis is undertaken
Additional exercises in most chapters
A summary of statistical formulas related to the specific designs used to teach the statistical concepts
This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.
Автор: MacInnes John Название: An Introduction to Secondary Data Analysis with IBM SPSS Statis ISBN: 1446285774 ISBN-13(EAN): 9781446285770 Издательство: Sage Publications Рейтинг: Цена: 6968.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: John MacInnes takes the fear out of statistics for students, and helps to raise the standards of their quantitative methods skills, by clearly and accessibly introducing all that`s needed to know about using secondary data and working with IBM SPSS Statistics.
This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background.
Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects.
This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.
Автор: Alfred Bartolucci, Karan P. Singh, Sejong Bae Название: Introduction to Statistical Analysis of Laboratory Data ISBN: 1118736869 ISBN-13(EAN): 9781118736869 Издательство: Wiley Рейтинг: Цена: 16466.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introduction to Statistical Analysis of Laboratory Data presents a detailed discussion of important statistical concepts and methods of data presentation and analysis
Provides detailed discussions on statistical applications including a comprehensive package of statistical tools that are specific to the laboratory experiment process
Introduces terminology used in many applications such as the interpretation of assay design and validation as well as "fit for purpose" procedures including real world examples
Includes a rigorous review of statistical quality control procedures in laboratory methodologies and influences on capabilities
Presents methodologies used in the areas such as method comparison procedures, limit and bias detection, outlier analysis and detecting sources of variation
Analysis of robustness and ruggedness including multivariate influences on response are introduced to account for controllable/uncontrollable laboratory conditions
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