Mathematical and statistical software

Some of the key mathematical results are stated without proof in order to make the underlying theory accessible to a wider audience.

With a growing number of scientists and engineers using JMP software for design of experiments, there is a need for an example-driven book that supports the most widely used textbook on the subject, Design and Analysis of Experiments by Douglas C.

Given the improved analytical capabilities of Excel, scientists and engineers everywhere are using it--instead of FORTRAN--to solve problems.

Learning a computer language like R can be either frustrating, fun, or boring.

IBM SPSS Statistics 26 Step by Step: A Simple Guide and Reference, sixteenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike.

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.

Learning a computer language like R can be either frustrating, fun, or boring.

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.

Numerical Python by Robert Johansson shows you how to leverage the numerical and mathematical modules in Python and its Standard Library as well as popular open source numerical Python packages like NumPy, FiPy, matplotlib and more to numerically compute solutions and mathematically model applications in a number of areas like big data, cloud computing, financial engineering, business management and more.

Big Data: A Tutorial-Based Approach explores the tools and techniques used to bring about the marriage of structured and unstructured data.

This textbook introduces the fundamental concepts and methods of statistical learning.

Compositional data are quantitative descriptions of the parts of some whole, conveying exclusively relative information.

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

The second edition of this textbook provides a comprehensive and detailed overview of MATLAB and specific tools for creating experiments and analysing data in psychology.

This book presents methods for computing correlation equations.

The SAS(R) Certified Specialist Prep Guide: Base Programming Using SAS(R) 9.

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

Enhance your SAS data-wrangling skills with high-precision and parallel data manipulation using the DS2 programming language.

This monograph focuses on the application of the solution strategy known as branch-and-bound to problems of combinatorial data analysis.

The first edition of this excellent handbook was extremely well received by both students and lecturers alike.

Group method of data handling (GMDH) is a typical inductive modeling method built on the principles of self-organization.

This book presents a general method for deriving higher-order statistics of multivariate distributions with simple algorithms that allow for actual calculations.

Little known to many, R works just as well with JavaScript-this book delves into the various ways both languages can work together.

If you know how to program, you're ready to tackle Bayesian statistics.

Introduces network inspired approaches for the analysis and integration of large, heterogeneous data sets in the life sciences.

Solve your pharmaceutical product development and manufacturing problems using JMP .

Winner of the 2024 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data.

Confidently navigate your JMP Scripting Language journey with this example-driven guide!

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years.

This book collects together selected peer-reviewed contributions presented at the European Conference on Data Analysis, ECDA 2022, held in Naples, Italy, September 14-16, 2022.

Practical numerical methods for solving differential equations are illustrated in the increasingly popular open source language R.

A comprehensive introduction to various numerical methods used in computational finance today Quantitative skills are a prerequisite for anyone working in finance or beginning a career in the field, as well as risk managers.

This practical guide is designed for students and researchers with an existing knowledge of R who wish to learn how to apply it in an epidemiological context and exploit its versatility.

This book presents the theory of matrix algebra for statistical applications, explores various types of matrices encountered in statistics, and covers numerical linear algebra.

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

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.

This book presents a systematic explanation of the SIML (Separating Information Maximum Likelihood) method, a new approach to financial econometrics.

Essential Mathematica: With Applications to Mathematics and Physics, based on the lecture notes of a course taught at the University of Illinois at Chicago to advanced undergrad and graduate students, teaches how to use Mathematica to solve a wide variety problems in mathematics and physics.

Point and click your way to performing statistics!

The official guide by the SAS Global Certification Program, SAS Certified Professional Prep Guide: Advanced Programming Using SAS 9.

This book presents the state of the art on numerical semigroups and related subjects, offering different perspectives on research in the field and including results and examples that are very difficult to find in a structured exposition elsewhere.