Struggling with S Plus? Consider alternative statistical software options.

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S Plus is commonly used in academic settings but can feel cumbersome for some users. Many participants recommend transitioning to R after completing their courses due to its broader user base and similar syntax to S Plus. R is favored in the statistics community, while SAS is preferred in biostatistics. Users also discuss the merits of Matlab for numerical computations, noting that it excels in engineering applications. Ultimately, the choice of software depends on specific fields and personal proficiency, with free and open-source software (FOSS) options often being sufficient for most statistical needs.
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I am using S Plus since it is the standard package for my course. I am finding it a bit clunky to use, still, after 6 months of on and off use. Does anyone else use S Plus?
 
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I think is not a bad choice for a course; the syntax of S is virtually identical to R, and R is the language I would deeply recommend you to learn if you are any serious about statistics. You can learn more about R in: http://www.r-project.org/
 
Yes, I think I will move to R after my course finishes. R has so many more users and most of the time when I google something for S-Plus the results are actually for R. The annoyance is that S-Plus is so similar that the techniques seem to mostly be the same but I can't guarantee code from R will run on S-Plus and vice-versa.

I currently have Maple as well and was looking at getting Matlab next year. It would be nice to use one package and language for both mathematics and statistics - any thoughts on why Matlab might be good/bad for both?
 
There is no one package to rule them all...

Matlab is virtually the standard among engineers and very good for numerical computations, Maple and also Mathematica compete in the symbolic mathematics arena and they both are quite good (in this case you need to figure out what field of mathematics you're interested into decide which package is better for you). Among people working in biostatistics SAS is also pretty much the standard in the industry but R is pretty much the standard among statisticians of any field...

So as you see, it depends on what field you are working and even the branch of that field. But anyway, my choice is:

FOSS

Statistics: R
Symbolic Math: Maxima
Numerical Math: Octave/Scilab

Commercial

Statistics: SAS, S-Plus, Statistica... Many others.
Symbolic Math: Mathematica/Maple
Numerical Math: Matlab

Though I find that once you are proficient with the FOSS packages you have no much use for the commercial ones and this is especially true for R.
 
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I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...

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