Weak in more cutting edge statistical procedures lacking in robust methods and survey methods Expensive/proprietaryĪppropriate for beginners Simple interfaces Commonly used in business & GovernmentĮxpensive. SPSS has incorporated a link to R, and SAS has protocols to move data and graphics between the two packages. Other packages have add-ons to connect with R. R connects with other languages (Java/C/JavaScript/Python/Fortran) & database systems, and other programs, SAS, SPSS, etc. Unparalleled question-and-answer (Q&A) websites. Extensibility: R supports extensions, e.g., for data manipulation, statistical modeling, and graphics.
If you change or redistribute the R source code, you have to make those changes available for anybody else to use. Anybody can access/review/extend the source code. Versatile for solving problems in many domains. Excellent connectivity to various types of data and other systems. R is actively maintained ( \(\ge 100,000\) developers, \(\ge 15K\) packages). The table below compares R to various other statistical analysis software packages and more detailed comparison is available online. Among these are R, Python, Java, C/C++, Perl, and many others. There are many different classes of software that can be used for data interrogation, modeling, inference and statistical computing.
0 kommentar(er)
