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In terms of statistical analyses all the general analytical tasks are performed well with SAS but its greatest strengths lie in its use of ANOVA which is a mixed model analysis that involves multivariate analytical methods. Also SAS has the ability to work with gargantuan data files as big as 32,768 variables while the number of records in mostly limited to the capability of one’s hard disk. So, power users who work with multiple files at once find this feature highly useful in SAS. Another advantage of SAS over Strata and SPSS is that it can work numerous data files at once. Also SAS includes proc sql thus, it allows one to run sql queries on the SAS data files. In the realm of data management SAS is highly efficient allowing users to manipulate data whichever way they want. So, evidently the process is more convoluted hence, if an error occurs it can be difficult to identify and correct it. The way SAS works while analyzing is that it first involves writing the SAS program then manipulating the data to perform their analysis.
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But as this is such a powerful programming package it is also often perceived as difficult to learn. SAS is the weapon of choice mostly for power users because of its programmability and prowess. The only greatest weakness of Strata is probably in the realm of variance and discriminant function analysis. This is also the weapon of choice for those who want to analyze survey data. Moreover, Strata also offer a nice range of robust methods that are very user-friendly like regression with robust standard errors, multinomial logistic regression and much more. In terms of the actual statistical analysis Strata is proficient in handling the general statistical analyses like regressions, survival analysis, factor analysis, multivariate analysis and logistic regression. But a drawback of Strata is that it primarily works with one data file at a time so, those who would like to work with multiple files at a time will find it an arduous practice. Many users like Strata better because it has several simple yet powerful data management commands that allow users to perform complicated manipulations of their data with relative ease. The aspect of data management is not as extensive with Stata as is with SAS. Another great advantage associated with Strata command is that it is very easy to diagnose an error and is also easy to amend them. People can also enter many commands at a time which is a mode most liked by power users. This is a mode that is highly preferred by beginners. The best advantage associated with Stata is its one line commands which can be used by entering one command at a time. This is often the statistical tool of choice for beginners and also power users alike because this is a very easy to learn software which is also powerful. But we as a statistical training institute have put up this post in a dispassionate and factual manner as much as possible and this comparison is by no means a comprehensive one. Before we begin that while several statisticians feel very passionately about the statistical software of their choice and often answer such questions with a biased perspective. So, let us begin by first giving you with a quick overview of each of these software’s style and general use. Now this question though asked frequently is still difficult to answer in one go as one might imagine that different packages have their own unique style and their own strengths and weaknesses. SPSS has also moved beyond its version 15.0+ and has also began adding different modules like its competitor SAS. But SPSS still comes with its popular “click and get results” interface.
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To begin with SAS is in its version 9+ and has also enhanced its visual appeal greatly. Both SPSS and SAS have been around in the world of statistical analysis for several years now, so, the conundrum of which is better software for statistical analysis is an age-old question among data people.