Mathematical and statistical software

Dieses Buch stellt erstmals im deutschsprachigen Raum die wichtigsten Kriterien für Datenqualität mit SPSS für Windows und Macintosh systematisch vor.

S+Functional Data Analysis is the first commercial object oriented package for exploring, modeling, and analyzing functional data.

This book introduces readers to statistical methodologies used to analyze doubly truncated data.

Master MATLAB(r) step-by-step The MATLAB-- "e;MATrix LABoratory"e;--computational environment offers a rich set of capabilities to efficiently solve a variety of complex analysis, simulation, and optimization problems.

Testing for economic convergence across countries has been a central issue in the literature of economic growth and development.

From a review of the first edition: "e;Modern Data Science with R.

Can artificial intelligence learn mathematics?

This book is a tutorial written by researchers and developers behind the FEniCS Project and explores an advanced, expressive approach to the development of mathematical software.

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics.

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously.

Algorithms for Computer Algebra is the first comprehensive textbook to be published on the topic of computational symbolic mathematics.

This volume collects selected, peer-reviewed contributions from the 2nd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Cadiz (Spain) between June 11-16 2014, and sponsored by the American Statistical Association, the Institute of Mathematical Statistics, the Bernoulli Society for Mathematical Statistics and Probability, the Journal of Nonparametric Statistics and Universidad Carlos III de Madrid.

Understanding Regression Analysis unifies diverse regression applications including the classical model, ANOVA models, generalized models including Poisson, Negative binomial, logistic, and survival, neural networks, and decision trees under a common umbrella -- namely, the conditional distribution model.

Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D.

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R.

This book features research contributions fromThe Abel Symposium on Statistical Analysis for High Dimensional Data, held inNyvagar, Lofoten, Norway, in May 2014.

The book is intended to serve as an introductory course in group theory geared towards second-year university students.

This textbook on computational statistics presents tools and concepts of univariate and multivariate statistical data analysis with a strong focus on applications and implementations in the statistical software R.

Industrial Statistics with MINITAB demonstrates the use of MINITAB as a tool for performing statistical analysis in an industrial context.

The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software.

R is a powerful and free software system for data analysis and graphics, with over 5,000 add-on packages available.

Explore essential quantum computing algorithms and master concepts intuitively with minimal math expertise requiredKey FeaturesLearn the fundamentals with an introduction to matrix arithmeticWrite quantum computing programs in Qiskit-IBM's publicly available quantum computing websiteEmail your questions directly to the author-no question is too elementaryPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionNavigate the quantum computing spectrum with this book, bridging the gap between abstract, math-heavy texts and math-avoidant beginner guides.

This comprehensive and stimulating introduction to Matlab, a computer language now widely used for technical computing, is based on an introductory course held at Qian Weichang College, Shanghai University, in the fall of 2014.

R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem.

This book collects peer-reviewed contributions on modern statistical methods and topics, stemming from the third workshop on Analytical Methods in Statistics, AMISTAT 2019, held in Liberec, Czech Republic, on September 16-19, 2019.

This book is about the role and potential of using digital technology in designing teaching and learning tasks in the mathematics classroom.

The new edition of this book provides an easily accessible introduction to the statistical analysis of network data using R.

This book is a valuable read for a diverse group of researchers and practitioners who analyze assessment data and construct test instruments.

Functional and Phylogenetic Ecology in R is designed to teach readers to use R for phylogenetic and functional trait analyses.

This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with the applications of Excel VBA, Python and R.

The book focuses on several skew-normal mixed effects models, and systematically explores statistical inference theories, methods, and applications of parameters of interest.

This book explores missing data techniques and provides a detailed and easy-to-read introduction to multiple imputation, covering the theoretical aspects of the topic and offering hands-on help with the implementation.

The Distributed and Unified Numerics Environment (Dune) is a set of open-source C++ libraries for the implementation of finite element and finite volume methods.

Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding and Applying Basic Statistical Methods Using R uniquely bridges the gap between advances in the statistical literature and methods routinely used by non-statisticians.

This book introduces academic researchers and professionals to the basic concepts and methods for characterizing interdependencies of multiple time series in the frequency domain.

R is rapidly growing in popularity as the environment of choice for data analysis and graphics both in academia and industry.

This book introduces the basic methodologies for successful data analytics.

Das Lehrbuch präsentiert ausführlich und durch viele Beispiele veranschaulicht den Einsatz von MATLAB und Simulink zur Darstellung und Berechnung in der Signalverarbeitung.

This is the first book to show the capabilities of Microsoft Excel to teach engineering statistics effectively.

Unstructured data is the most voluminous form of data in the world, and several elements are critical for any advanced analytics practitioner leveraging SAS software to effectively address the challenge of deriving value from that data.

Increasing the designer's con dence that a piece of software or hardwareis c- pliant with its speci cation has become a key objective in the design process for software and hardware systems.

Mathematica(R): A Problem-Centered Approach introduces the vast array of features and powerful mathematical functions of Mathematica using a multitude of clearly presented examples and worked- out problems.