Mathematical and statistical software

A hands-on guide to using Excel in the business context First published in 2012, Using Excel for Business and Financial Modelling contains step-by-step instructions of how to solve common business problems using financial models, including downloadable Excel templates, a list of shortcuts and tons of practical tips and techniques you can apply straight away.

This is the first book to show the capabilities of Microsoft Excel to teach biological and life sciences statistics effectively.

This edited book presents the recent developments in partial least squares-path modeling (PLS-PM) and provides a comprehensive overview of the current state of the most advanced research related to PLS-PM.

The R Companion to Elementary Applied Statistics includes traditional applications covered in elementary statistics courses as well as some additional methods that address questions that might arise during or after the application of commonly used methods.

Get started computing with data.

This textbook presents the essential tools and core concepts of data science to public officials, policy analysts, and economists among others in order to further their application in the public sector.

Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts.

Can artificial intelligence learn mathematics?

This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena.

This introductory textbook for business statistics teaches statistical analysis and research methods via business case studies and financial data using Excel, Minitab, and SAS.

This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis.

Praise for previous editions:"e;Gandrud has written a great outline of how a fully reproducible research project should look from start to finish, with brief explanations of each tool that he uses along the way.

Today, certain computer software systems exist which surpass the computational ability of researchers when their mathematical techniques are applied to many areas of science and engineering.

This volume presents theoretical developments, applications and computational methods for the analysis and modeling in behavioral and social sciences where data are usually complex to explore and investigate.

Using Applied Econometrics with SAS: Modeling Demand, Supply, and Risk, you will quickly master SAS applications for implementing and estimating standard models in the field of econometrics.

This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics.

Advance your skills in building predictive models with SAS!

This book focuses on the application and development of information geometric methods in the analysis, classification and retrieval of images and signals.

This book brings together the best contributions of the Applied Statistics and Policy Analysis Conference 2019.

Features a simplified presentation of numerical methods by introducing and implementing SAGE programs An Introduction to SAGE Programming: With Applications to SAGE Interacts for Numerical Methods emphasizes how to implement numerical methods using SAGE Math and SAGE Interacts and also addresses the fundamentals of computer programming, including if statements, loops, functions, and interacts.

John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award.

This book provides state-of-the-art and interdisciplinary topics on solving matrix eigenvalue problems, particularly by using recent petascale and upcoming post-petascale supercomputers.

Big data: It's unstructured, it's coming at you fast, and there's lots of it.

This book focuses on recent advances, approaches, theories and applications related to mixture models.

Foreword by Oliver Schabenberger, PhDExecutive Vice President, Chief Operating Officer and Chief Technology OfficerSASDive into deep learning!

Geocomputation with Python is a comprehensive resource for working with geographic data with the most popular programming language in the world.

This book of peer-reviewed short papers on methodological and applied statistics and demography is the third of four volumes from the 52nd Scientific Meeting of the Italian Statistical Society (SIS 2024), held in Bari, Italy, on June 17-20, 2024.

Explore biostatistics using JMP(R) in this refreshing introductionPresented in an easy-to-understand way, Introduction to Biostatistics with JMP introduces undergraduate students in the biological sciences to the most commonly used (and misused) statistical methods that they will need to analyze their experimental data using JMP.

This book on statistical disclosure control presents the theory, applications and software implementation of the traditional approach to (micro)data anonymization, including data perturbation methods, disclosure risk, data utility, information loss and methods for simulating synthetic data.

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 book shows you how to analyze data sets systematically and to use the R Commander to extract information from data almost effortlessly.

Clustering and Classification, Data Analysis, Data Handling and Business Intelligence are research areas at the intersection of statistics, mathematics, computer science and artificial intelligence.

The authors explain at length the principles of chemical kinetics and approaches to computerized calculations in modern software suites - mathcad and maple.

Learn how to access analytics from SAS Cloud Analytic Services (CAS) using R and the SAS Viya platform.

This book evolved from lectures, courses and workshops on missing data and small-area estimation that I presented during my tenure as the ?

Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data.

Discover the power of mixed models with SAS.

This book aims to explain how to use R to perform morphometrics.

The Encyclopaedia of Discrete Mathematics presents a through, Comprehensive Treatment of the subject using a Flexible Modular format.

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.

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field.

Economic Modeling Using Artificial Intelligence Methods examines the application of artificial intelligence methods to model economic data.