# Re: SV: For those in need of running SAS using an SPSSfile

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## Re: SV: For those in need of running SAS using an SPSSfile

 I'm sure that you'd agree with me that it's patently obvious that the SPSS programming language hardly compares to SAS' SAS/IML module.  There's simply no such comparison.  SAS's matrix programming language is far superior to SPSS' matrix programming language. And the question still remains: why do most statisticians choose SAS over SPSS?  You tell me why such is the case.  Have you been a statistics student in a graduate level program * or a mathematics student? >>> "Peck, Jon" <[hidden email]> 7/18/2006 12:37 PM >>> First, let's correct the facts.  SPSS in fact does have a matrix language built in.  It has 18 statement types, 59 functions, and 20 operators.  Users on this list have posted extensive programs using it. Second, using the programmability features of SPSS 14, you have access to a vast array of scientifically oriented modules from third parties.  For example, scipy and numpy can be downloaded free and used within SPSS. Here is the summary description of scipy SciPy is an open source library of scientific tools for Python. SciPy gathers a variety of high level science and engineering modules together as a single package. SciPy provides modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, genetic algorithms, ODE solvers, special functions, and more. SciPy requires and supplements NumPy, which provides a multidimensional array object and other basic functionality. Here are a few random examples of simple things you can do with this library within BEGIN PROGRAM in SPSS.  Since you can read the SPSS cases and output in this mode, the inputs can be anything in SPSS. factorial and combination functions: import scipy scipy.factorial(4)  -> array(24.0) int(scipy.factorial(4)) -> 24 scipy.factorial(4.1) -> array(27.931753738368371)  (Gamma function) scipy.factorial(50, exact=1)  -> 30414093201713378043612608166064768844377641568960512000000000000L matrix operations: import scipy A = scipy.mat('[1 3 5;2 5 1;2 3 8]') print A -> matrix [[1 3 5]  [2 5 1]  [2 3 8]] print A.I -> matrix([[-1.48,  0.36,  0.88], [ 0.56,  0.08, -0.36],  [ 0.16, -0.12,  0.04]]) (A * A.I = identity matrix) scipy.linalg.det(A) -> -25 solving linear equations (nonlinear also available): from scipy import * A= mat('[1 3 5;2 5 1;2 3 8]') b = mat('[10;8;3]') Solve linear equations Ax = b... A.I*b or linalg.solve(A,b) Regards, Jon Peck SPSS -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Joseph Teitelman temp2 Sent: Tuesday, July 18, 2006 9:15 AM To: [hidden email] Subject: Re: [SPSSX-L] SV: For those in need of running SAS using an SPSS file [snip] Next, Stat/IML is a matrix  programming language which comes along with SAS.  It is extremely powerful.  SPSS has no matrix programming language.  And from what I've been told, neither does Stata. [>>>Peck, Jon] [snip] Those were my impressions. Joe Teitelman
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## Re: SV: For those in need of running SAS using an SPSSfile

 As a matter of fact, I do not agree with you in the slightest when you consider the power of the open source modules that can be plugged in to SPSS via programmability and combined with the power and elegance of the Python language and the SPSS engine.  Maybe you should try it. And as another matter of fact, I happen to have a Ph. D. in Economics (econometrics), and taught in a top-tier university in the Economics and Statistics departments for 13 years before joining SPSS. I have no interest in badmouthing SAS or other competing products.  Each has strengths and weaknesses.  Instead, I try to learn what those are. -Jon Peck SPSS -----Original Message----- From: Joseph Teitelman temp2 [mailto:[hidden email]] Sent: Tuesday, July 18, 2006 12:30 PM To: [hidden email]; Peck, Jon Subject: Re: SV: For those in need of running SAS using an SPSSfile I'm sure that you'd agree with me that it's patently obvious that the SPSS programming language hardly compares to SAS' SAS/IML module.  There's simply no such comparison.  SAS's matrix programming language is far superior to SPSS' matrix programming language. And the question still remains: why do most statisticians choose SAS over SPSS?  You tell me why such is the case.  Have you been a statistics student in a graduate level program * or a mathematics student? >>> "Peck, Jon" <[hidden email]> 7/18/2006 12:37 PM >>> First, let's correct the facts.  SPSS in fact does have a matrix language built in.  It has 18 statement types, 59 functions, and 20 operators.  Users on this list have posted extensive programs using it. Second, using the programmability features of SPSS 14, you have access to a vast array of scientifically oriented modules from third parties.  For example, scipy and numpy can be downloaded free and used within SPSS. Here is the summary description of scipy SciPy is an open source library of scientific tools for Python. SciPy gathers a variety of high level science and engineering modules together as a single package. SciPy provides modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, genetic algorithms, ODE solvers, special functions, and more. SciPy requires and supplements NumPy, which provides a multidimensional array object and other basic functionality. Here are a few random examples of simple things you can do with this library within BEGIN PROGRAM in SPSS.  Since you can read the SPSS cases and output in this mode, the inputs can be anything in SPSS. factorial and combination functions: import scipy scipy.factorial(4)  -> array(24.0) int(scipy.factorial(4)) -> 24 scipy.factorial(4.1) -> array(27.931753738368371)  (Gamma function) scipy.factorial(50, exact=1)  -> 30414093201713378043612608166064768844377641568960512000000000000L matrix operations: import scipy A = scipy.mat('[1 3 5;2 5 1;2 3 8]') print A -> matrix [[1 3 5]  [2 5 1]  [2 3 8]] print A.I -> matrix([[-1.48,  0.36,  0.88], [ 0.56,  0.08, -0.36],  [ 0.16, -0.12,  0.04]]) (A * A.I = identity matrix) scipy.linalg.det(A) -> -25 solving linear equations (nonlinear also available): from scipy import * A= mat('[1 3 5;2 5 1;2 3 8]') b = mat('[10;8;3]') Solve linear equations Ax = b... A.I*b or linalg.solve(A,b) Regards, Jon Peck SPSS -----Original Message----- From: SPSSX(r) Discussion [mailto:[hidden email]] On Behalf Of Joseph Teitelman temp2 Sent: Tuesday, July 18, 2006 9:15 AM To: [hidden email] Subject: Re: [SPSSX-L] SV: For those in need of running SAS using an SPSS file [snip] Next, Stat/IML is a matrix  programming language which comes along with SAS.  It is extremely powerful.  SPSS has no matrix programming language.  And from what I've been told, neither does Stata. [>>>Peck, Jon] [snip] Those were my impressions. Joe Teitelman
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## Re: SV: For those in need of running SAS using an SPSSfile

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