Applied Mathematica: Getting Started, Getting It Done
| Author | : | |
| Rating | : | 4.37 (591 Votes) |
| Asin | : | 020154217X |
| Format Type | : | paperback |
| Number of Pages | : | 448 Pages |
| Publish Date | : | 2013-11-28 |
| Language | : | English |
DESCRIPTION:
After presenting a "quick start" chapter designed to get up and running with Mathematica, the authors show how Mathematica can be used as a data analysis and visualization system. 020154217XB04062001 . Topics in this section include importing information to Mathematica, organizing information, visualizing data in both 2-D and 3-D, processing information, and exporting results from Mathematica. Next, the authors guide you through programming in Mathematica. From the Back Cover As an applied scientist you are constantly looking for new and better ways to solve problems. Included here are topics such as programming styles, important built-in structures, function definitions, procedural methods, rule-based schemes and iteration, contexts and packages, and increasing efficiency. This book shows how MathematicaAE, the powerful mathematical software system, can be used to solve problems in the applied sciences.Written by two authors who have been teaching Mat
Best long term reference on Mathematica Clifford Martin I've been using this book since 1995. I use version 4.2 of Mathematica now and the fact that Shaw and Tigg wrote it for 2.2 doesn't matter. It teaches ways of thinking about problems in Mathematica that most other books don't even try. I use Mathematica almost daily in my professional life. If I run into a problem with applying Mathematica I invariably end up using Shaw and Tigg(I have 6 or. Jihwan Myung said mathematica can do data analysis. This book is rather strong on data analysis. (linear regression, scattergram, etc.) It also explains various methods (both "mathematica can do data analysis" according to Jihwan Myung. This book is rather strong on data analysis. (linear regression, scattergram, etc.) It also explains various methods (both 2D and mathematica can do data analysis This book is rather strong on data analysis. (linear regression, scattergram, etc.) It also explains various methods (both 2D and 3D) to graphically present such analyses. (e.g. fourier filtering, graphs with lots of interesting diagrams, etc.) I am sure social science people will enjoy this book. Plenty of examples to let you get on track quickly. However, rather weak on explaining theoret. D) to graphically present such analyses. (e.g. fourier filtering, graphs with lots of interesting diagrams, etc.) I am sure social science people will enjoy this book. Plenty of examples to let you get on track quickly. However, rather weak on explaining theoret. D and mathematica can do data analysis This book is rather strong on data analysis. (linear regression, scattergram, etc.) It also explains various methods (both 2D and 3D) to graphically present such analyses. (e.g. fourier filtering, graphs with lots of interesting diagrams, etc.) I am sure social science people will enjoy this book. Plenty of examples to let you get on track quickly. However, rather weak on explaining theoret. D) to graphically present such analyses. (e.g. fourier filtering, graphs with lots of interesting diagrams, etc.) I am sure social science people will enjoy this book. Plenty of examples to let you get on track quickly. However, rather weak on explaining theoret. outdated but still useful as introduction I found it quite useful to gather the necessay skills to start Mathematica, though it is rapidly becoming outdated and certainly lacks any in depth commands.
Included here are topics such as programming styles, important built-in structures, function definitions, procedural methods, rule-based schemes and iteration, contexts and packages, and increasing efficiency.Also included is a separate section detailing several case studies that explore and apply Mathematica to particular areas. 020154217XB04062001. Topics in this section include importing information to Mathematica, organizing information, visualizing data in both 2-D and 3-D, processing information, and exporting results from Mathematica. After presenting a "quick start" chapter des