## subcategories

**MATLAB** (19)

**R Programming Language** (14)

## e-books in Mathematical & Statistical Software category

**Introduction to GNU Octave**

by

**Jason Lachniet**-

**Wytheville Community College**,

**2017**

A brief introduction to scientific computing with Gnu Octave. Designed as a textbook supplement for freshman and sophomore linear algebra and calculus students. It is heavy on linear algebra and makes a good supplement to a linear algebra textbook.

(

**10743**views)

**wxMaxima for Calculus I and II**

by

**Zachary Hannan**,

**2015**

These books introduce the free computer algebra system wxMaxima in the context of single variable calculus. Each book can serve as a lab manual for a one-unit semester calculus lab, a source of supplemental CAS exercises or a tutorial reference.

(

**6080**views)

**Mathematica Programming: An Advanced Introduction**

by

**Leonid Shifrin**-

**mathprogramming-intro.org**,

**2009**

When writing this book I had in mind people who want to understand Mathematica programming, and particularly those users who would like to make a transition from a user to a programmer, or perhaps those who already have some limited experience.

(

**8990**views)

**Octave Programming Tutorial**

by

**Henri Amuasi**-

**Wikibooks**,

**2012**

Octave is a high-level language, primarily intended for numerical computations. The purpose of this collection of tutorials is to get you through most (and eventually all) of the available Octave functionality from a basic level.

(

**8620**views)

**Maple**

by

**Alain Le Stang**-

**Wikibooks**,

**2012**

Maple is a computer algebra system offering many possibilities for math problems. Users can enter mathematics in traditional mathematical notation. This book aims to give all tools needed to be autonomous with this software.

(

**7688**views)

**LAPACK Users' Guide**

by

**E. Anderson, et al.**,

**1999**

LAPACK is a library of numerical linear algebra subroutines designed for high performance. The book provides an introduction to the design of the LAPACK package, a detailed description of its contents, reference manuals, and example programs.

(

**8137**views)

**AMPL: A Modeling Language for Mathematical Programming**

by

**R. Fourer, D.M. Gay, B.W. Kernighan**-

**Duxbury Press**,

**2002**

AMPL is a language for large-scale optimization and mathematical programming problems in production, distribution, blending, scheduling, and many other applications. This book is a complete guide for modelers at all levels of experience.

(

**14831**views)

**Using SPSS and PASW**

by

**Caitlin McGrath, et al.**-

**Wikibooks**,

**2011**

SPSS is a software program widely used in the social sciences. This book is a rudimentary introduction to the use of SPSS for basic statistical analysis. The book is written with a focus on social scientific analysis in mind, particularly Sociology.

(

**9607**views)

**Advanced Scientific Computing**

by

**Zdzislaw Meglicki**-

**Indiana University**,

**2001**

Topics: linear algebra and fast Fourier transform packages and algorithms, Message Passing Interface (MPI) and parallel I/O (MPI/IO), 3D visualisation of scientific data sets, implementation of problem solving environments, quantum computing.

(

**11714**views)

**SPSS: Stats Practically Short and Simple**

by

**Sidney Tyrrell**-

**BookBoon**,

**2009**

This textbook is for people who want to know how to use SPSS for analyzing data. The author has considerable experience of teaching many such people and assumes they know the basics of statistics but nothing about SPSS, or as it is now known, PASW.

(

**15241**views)

**Axiom: The Scientific Computation System**

by

**Richard D. Jenks, Robert S. Sutor**-

**axiom-developer.org**,

**2003**

Axiom is a free general purpose computer algebra system. The book gives a technical introduction to AXIOM, interacts with the system's tutorial, accesses algorithms developed by the symbolic computation community, and presents advanced techniques.

(

**23507**views)

**Modeling with Data: Tools and Techniques for Scientific Computing**

by

**Ben Klemens**-

**Princeton University Press**,

**2009**

The author explains how to execute computationally intensive analysis on large data sets, showing how to determine the best methods. The book will interest researchers and graduates in the social sciences, engineering, economics, and mathematics.

(

**16726**views)

**The Mathematica Book**

by

**Stephen Wolfram**-

**Wolfram Media**,

**2003**

A tutorial and a definitive reference for Mathematica users, it covers all aspects of Mathematica. An essential resource for all users, from beginners to experts, providing the internet community full access to its encyclopedic knowledge base.

(

**17984**views)