From the UCLA, Statistics Department: Many people ask us about the differences between SAS, Stata and SPSS or which package is the best package.  As you might imagine, each package has its own unique style and its own strengths and weaknesses. This page gives a quick overview of the style of each of the packages and the strengths and weaknesses of each, but this is by no means a comprehensive comparison of the packages. Sometimes people feel very passionately about the statistical packages they use; we hope most will agree that this is a factual and dispassionate comparison of these packages.




Overall Summary

Each package offers its own unique strengths and weaknesses.  As a whole, SAS, Stata and SPSS form a set of tools that can be used for a wide variety of statistical analyses.  With Stat/Transfer it is very easy to convert data files from one package to another in just a matter of seconds or minutes.  Therefore, there can be quite an advantage to switching from one analysis package to another depending on the nature of your problem.  For example, if you were performing analyses using mixed models you might choose SAS, but if you were doing logistic regression you might choose Stata, and if you were doing analysis of variance you might choose SPSS. If you are frequently performing statistical analyses, we would strongly urge you to consider making each one of these packages part of your toolkit for data analysis.