Within the world of data science and statistics, there are four major statistical software packages that allow researchers to organize, analyze, understand and visualize data sets. These programs include the R Project for Statistical Computing (and RStudio), Python (and the Spyder and Jupyter notebook IDEs), Stata and the Statistical Package for the Social Sciences (SPSS).
Each of these packages has distinctive strengths and weaknesses, and some software packages are typically used in certain applications, such as R and Python being more typically seen in physical sciences and business, Stata mostly used in economics and finance, and SPSS often utilized in social sciences and marketing research.
Given that each of these packages is in demand for different applications and many people in the business or research world require more than one package, successful data scientists often seek to develop skills in multiple packages.
Our site provides many resources for each of these four statistical packages, beginning with detailed guides to Installing R, Python, Stata and SPSS on your computer and running Basic Statistics in each program. For a deeper dive into each program, we have more detailed tutorials to running analyses in each program, which you can access using the links below.
If you want a more in-depth look into each of these programs, make sure to check out our reviews of the Top 5 Books in Data Science and Statistics and our detailed listing of Online Data Science Courses.
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