Mathematical and statistical software

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods.

Studies of evolution at the molecular level have experienced phenomenal growth in the last few decades, due to rapid accumulation of genetic sequence data, improved computer hardware and software, and the development of sophisticated analytical methods.

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting.

Gain Deeper Insights, Make Smarter Decisions, and Earn More Profits It's time to put the full power of Excel quantitative analysis behind your management decisions!

This is today's most complete guide to regression analysis with Microsoft(R) Excel for any business analytics or research task.

This is today's most complete guide to regression analysis with Microsoft(R) Excel for any business analytics or research task.

Today, successful firms compete and win based on analytics.

This Element is an excerpt from Ubiquitous Computing for Business: Find New Markets, Create Better Businesses, and Reach Customers Around The World 24-7-365 (9780137064434) by Bo Begole.

This Element is an excerpt from Ubiquitous Computing for Business: Find New Markets, Create Better Businesses, and Reach Customers Around The World 24-7-365 (9780137064434) by Bo Begole.

This Element is an excerpt from Ubiquitous Computing for Business: Find New Markets, Create Better Businesses, and Reach Customers Around The World 24-7-365 (9780137064434) by Bo Begole.

This book presents a study of the COVID-19 pandemic using computational social scientific analysis that draws from, and employs, statistics and simulations.

This innovative textbook presents material for a course on modern statistics that incorporates Python as a pedagogical and practical resource.

This book illustrates the potential for computer simulation in the study of modern slavery and worker abuse, and by extension in all social issues.

The quantity, diversity and availability of transport data is increasing rapidly, requiring new skills in the management and interrogation of data and databases.

The contributions gathered in this book focus on modern methods for statistical learning and modeling in data analysis and present a series of engaging real-world applications.

This textbook, now in its second edition, provides a broad introduction to the theory and practice of both continuous and discrete dynamical systems with the aid of the Mathematica software suite.

This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain.

This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics.

Get to grips with building robust XGBoost models using Python and scikit-learn for deploymentKey FeaturesGet up and running with machine learning and understand how to boost models with XGBoost in no timeBuild real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal resultsDiscover tips and tricks and gain innovative insights from XGBoost Kaggle winnersBook DescriptionXGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently.

Solve real-world statistical problems using the most popular R packages and techniquesKey FeaturesLearn how to apply statistical methods to your everyday research with handy recipesFoster your analytical skills and interpret research across industries and business verticalsPerform t-tests, chi-squared tests, and regression analysis using modern statistical techniquesBook DescriptionR is a popular programming language for developing statistical software.

MatLab, Third Edition is the only book that gives a full introduction to programming in MATLAB combined with an explanation of the software's powerful functions, enabling engineers to fully exploit its extensive capabilities in solving engineering problems.

This new textbook in signals and systems provides a pedagogically rich approach to what can commonly be a mathematically dry subject.

Today, information technology plays a pivotal role in financial control and audit: most financial data is now digitally recorded and dispersed among servers, clouds and networks over which the audited firm has no control.

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

The essential guide to MATLAB as a problem solving tool This text presents MATLAB both as a mathematical tool and a programming language, giving a concise and easy to master introduction to its potential and power.

Learn window function foundational concepts through a cookbook-style approach, beginning with an introduction to the OVER() clause, its various configurations in terms of how partitions and window frames are created, and how data is sorted in the partition so that the window function can operate on the partition data sets.

Learn window function foundational concepts through a cookbook-style approach, beginning with an introduction to the OVER() clause, its various configurations in terms of how partitions and window frames are created, and how data is sorted in the partition so that the window function can operate on the partition data sets.

Teaches students how to use SPSS to conduct the statistical analyses most commonly used in political science.

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences.

This book helps the reader make use of the mathematical models of biological phenomena starting from the basics of programming and computer simulation.

The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R for marketing research.

Spatial Data Science introduces fundamental aspects of spatial data that every data scientist should know before they start working with spatial data.

This book provides an introduction to chemical engineering analysis- which reviews the processes and designs used to manufacture, use, and dispose of chemical products-and to Mathematica, one of the most powerful mathematical software tools available for symbolic, numerical, and graphical computing.

The third edition of the Student Study Guide With IBM(R) SPSS(R) Workbook for Research Methods, Statistics, and Applications by Kathrynn A.

The Third Edition of the Differential Equations with Mathematica integrates new applications from a variety of fields,especially biology, physics, and engineering.

Maple by Example, Third Edition, is a reference/text for beginning and experienced students, professional engineers, and other Maple users.

Adaptive filtering still receives attention in engineering as the use of the adaptive filter provides improved performance over the use of a fixed filter under the time-varying and unknown statistics environments.

Computing with Mathematica, Second Edition is engaging and interactive.

This textbook offers an essential introduction to survey research and quantitative methods with clear instructions on how to conduct statistical tests with R.

R for Quantitative Chemistry is an exploration of how the R language can be applied to a wide variety of problems in what is typically termed "e;Quantitative Chemistry"e; or sometimes "e;Analytical Chemistry"e;.

Software Design for Engineers and Scientists integrates three core areas of computing:.

This book, using R and RStudio, demonstrates how to render an audit opinion that is legally and statistically defensible; analyze, extract, and manipulate accounting data; build a risk assessment matrix to inform the conduct of a cost-effective audit program; and more.

For all engineers and students coming to finite element analysis or to ANSYS software for the first time, this powerful hands-on guide develops a detailed and confident understanding of using ANSYS's powerful engineering analysis tools.

A step-by-step guide that demonstrates how to build simple-to-advanced applications through examples in Julia Lang 1.

A practical, professional guide to MATLAB computational techniques and engineering applicationsMATLAB Numerical Methods with Chemical Engineering Applications shows you, step by step, how to use MATLAB to model and simulate physical problems in the chemical engineering realm.

This book explores how deep learning enhances statistical methods for hypothesis testing, point estimation, optimization, interpretation, and other aspects.

This book is an introduction to Python for intermediate learners.

This book is an introduction to Python for intermediate learners.

The goals of this new, second edition of this book are to develop the skills and an appreciation for the richness and versatility of modern time series analysis as a tool for analyzing dependent data.