On this blog i frequently feature examples from Stata, but also from SPSS, Microsoft Excel and R Studio. They are all are popular software tools used for data analysis and statistical modeling (and yes, especially Excel have a lot of other use cases). In this post I'm gonna give a somewhat rudimentary, comparative summary of each of the statistics packages and their differences. I'm also gonna contrast them against Excel as it can sometimes be a viable alternative depending on the use case.
Stata is a general-purpose statistical software package used in social sciences research. It has a comprehensive set of statistical tools, including regression analysis, survival analysis, and panel data analysis. Stata is known for its speed and ease of use, and it has a large user community and extensive documentation. Compared to Microsoft Excel, Stata is more powerful and specialized for data analysis tasks. Personally I am a fan of the minimalistic GUI and the command line tool which is why Stata tends to be my preferred choice most in most situations.
SPSS is a statistical software package used in social sciences research, marketing research, and data mining. It has a wide range of statistical tools, including regression analysis, factor analysis, and clustering. SPSS is known for its ease of use and flexibility, and it has a large user community and extensive documentation. Compared to Microsoft Excel, SPSS has a more focused set of statistical tools and is more specialized for data analysis tasks. I have not used SPSS that much myself, it's certainly powerful but i'm particularly not a fan of the GUI, among other things.
R Studio is an open-source statistical software package used in data science and statistical modeling. It has a wide range of statistical tools, including linear and nonlinear modeling, time-series analysis, and machine learning. R Studio is very extensible, as it has a large library of packages for various statistical techniques and data visualization. As the others, when compared to Microsoft Excel, R Studio is more specialized and powerful for data analysis tasks. I've been getting into R Studio a lot lately, i really like the fact that it's open source with a very vibrant and active community. The GUI is more reminiscent of an IDE so if you have a programming background you will instantly feel more at home compared to the other options discussed here.
Lastly, I want to mention Excel while not a dedicated statistics package, still has some powerful features including data manipulation, formula calculation, and charting. Therefore it can sometimes be used as an alternative to the other dedicated statistics packages. Compared to Stata, SPSS, and R Studio, Excel is less specialized and powerful for data analysis tasks, but it is more allround and has a faster pace of development (compared to some of the outhers at least): There's also the cloud integration aspect which is a competitive advantage as well.
So to summarize, Stata, SPSS, and R Studio are more specialized and powerful for data analysis tasks, while Microsoft Excel is more versatile and commonly used for a variety of tasks beyond data analysis. The choice of software is dependent on the use case of course, but for less complex situations i would recommend Stata or Excel.