Mathematica Data Visualization was written with one goal in mind—teaching
the reader how to write interactive visualization programs seamlessly using
Mathematica. Mathematica is the programming language of choice for many
data analysts, mathematicians, scientists, engineers, and business analysts.
It offers a powerful suite of data analysis and data mining packages, along
with a very rich data visualization framework for its users.

The aim of The Book of R: A First Course in Programming
and Statistics is to provide a relatively gentle yet informative
exposure to the statistical software environment
R, alongside some common statistical analyses,
so that readers may have a solid foundation

Game theory has become an essential tool in the analysis of supply chains with multiple
agents, often with conflicting objectives. This chapter surveys the applications of game theory
to supply chain analysis and outlines game-theoretic concepts that have potential for future
application. We discuss both non-cooperative and cooperative game theory in static and
dynamic settings. Careful attention is given to techniques for demonstrating the existence
and uniqueness of equilibrium in non-cooperative games. A newsvendor game is employed
throughout to demonstrate the application of various tools.

Optimization problems arise naturally in many application fields. Whatever people do, at
some point they get a craving to organize things in a best possible way. This intention,
converted in a mathematical form, turns out to be an optimization problem of certain type.
Depending on the field of interest, it could be the optimal design problem, the optimal
control problem, the optimal location problem or even the optimal diet problem.

Optimization has been expanding in all directions at an astonishing rate
during the last few decades. New algorithmic and theoretical techniques have
been developed, the diffusion into other disciplines has proceeded at a rapid
pace, and our knowledge of all aspects of the field has grown even more
profound. At the same time, one of the most striking trends in optimization is
the constantly increasing emphasis on the interdisciplinary nature of the field.
Optimization has been a basic tool in all areas of applied mathematics,
engineering, medicine, economics and other sciences.

This book is intended as a text covering the central concepts of practical optimization
techniques. It is designed for either self-study by professionals or classroom work at
the undergraduate or graduate level for students who have a technical background
in engineering, mathematics, or science. Like the field of optimization itself,
which involves many classical disciplines, the book should be useful to system
analysts, operations researchers, numerical analysts, management scientists, and
other specialists from the host of disciplines from which practical optimization applications
are drawn. The prerequisites for convenient use of the book are relatively
modest; the prime requirement being some familiarity with introductory elements
of linear algebra. Certain sections and developments do assume some knowledge
of more advanced concepts of linear algebra, such as eigenvector analysis, or some
background in sets of real numbers, but the text is structured so that the mainstream
of the development can be faithfully pursued without reliance on this more advanced
background material.

This chapter is a self-contained tutorial which tells you how to get
started with parallel programming and how to design and implement
algorithms in a structured way. The chapter introduces a simple target
architecture for designing parallel algorithms, the bulk synchronous
parallel computer. Using the computation of the inner product of two
vectors as an example, the chapter shows how an algorithm is designed
hand in hand with its cost analysis. The algorithm is implemented
in a short program that demonstrates the most important primitives
of BSPlib, the main communication library used in this book. If you
understand this program well, you can start writing your own parallel
programs. Another program included in this chapter is a benchmarking
program that allows you to measure the BSP parameters of your
parallel computer. Substituting these parameters into a theoretical cost
formula for an algorithm gives a prediction of the actual running time
of an implementation.

There are so many computer languages you can use to
get started with coding. What you’ll find in this book is an
introductory treatment of coding in a single programming
language — a teaching language, called MicroWorlds EX, that
is conceptually transferrable to every other programming
language. It’s easy to learn because the vocabulary and
punctuation look like regular words and symbols. And it’s fun to
do because you can add graphics, motion, and sound to make
your projects into real apps.