Advice on Choosing a CAS - Mathematica, Maple, Derive, Matlab

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Discussion Overview

The discussion revolves around selecting a Computer Algebra System (CAS) for learning purposes, specifically considering options like Mathematica, Maple, Derive, Matlab, and open-source alternatives. The focus includes potential applications in calculus, statistics, and linear algebra.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant seeks advice on which CAS to choose for learning, mentioning several options.
  • Another participant questions the intended use of the CAS, suggesting that the choice may depend on whether the focus is on calculus, statistics, or linear algebra.
  • A participant argues that a CAS may not be necessary for calculus, suggesting that a scientific calculator could suffice, but recommends Maple for general CAS learning due to its public release of algorithms.
  • Open-source alternatives like Octave and Scilab are proposed for numerical tasks, with a note that they use Matlab-like syntax and are suitable for linear algebra operations.
  • One participant expresses a preference for Octave and mentions its modularity and support for external programming languages, while also noting its graphing capabilities through gnuplot.
  • Another participant highlights that Scilab offers features like real-time rotations and zooming in graphing, which they find superior to gnuplot.
  • A viewpoint is presented that emphasizes the importance of learning numerical calculations over using a CAS, suggesting that CAS may be considered pointless for certain applications.

Areas of Agreement / Disagreement

Participants express differing opinions on the necessity of a CAS for calculus and the suitability of various software options. There is no consensus on which CAS is the best choice, and multiple competing views remain regarding the utility of CAS versus numerical methods.

Contextual Notes

Some limitations include the lack of clarity on specific use cases for the CAS, as well as varying definitions of what constitutes essential features in a CAS. The discussion does not resolve the effectiveness of different systems for learning purposes.

agro
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I'm planning to learn a CAS. Can you guys give me advice on what I should choose (Mathematica, Maple, Derive, Matlab, or maybe others)?

Thanks a lot.
 
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What do you want to do with this knowledge you plan to learn? Calculus? Stats? Linear Algebra?
 
In the short term, calculus...
 
You don't need a CAS for calculus. A scientific calculator will do fine, however, if you want to learn a CAS in general, I'd pick Maple.

Maple releases all their algorithms to the general public, but Mathematica does not.

If the symbolic functions aren't essential, I'll suggest a few open-source altenatives: octave and scilab. Both, octave and scilab, use Matlab-like syntax. Octave and scilab are more for doing numerical tasks, rather than evaluating an integral symbolically.

octave and scilab are great for doing linear algebra tasks: eigenvalues, matrice operations, and such. I've solved a few ODE's and PDE's numerically on them for fun. octave is a rather modular application. It supports writing programs or "external" functions in Java, C, and C++, in addition to its on C-like language. Octave is totally GPL'd, whereas scilab is nondistributable but open-source (?).

scilab and octave support graphing, also. Octave interfaces with an application called "gnuplot", which supports all the methods of graphing that the propiertary CAS's (Mathematica, Maple, etc.) support. I'm not as familiar with scilab but it uses something *very* similar to gnuplot. I actually like the plotting features of scilab slightly better than those of gnuplot. Scilab supports real-time rotations and zooming, whereas gnuplot does not. Mathematica doesn't either.

Learning how to use the computer for numerical calculations is all what the computer is about; I find the CAS to be pointless.
 
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