Hello Layth,

My belief is that these questions likely have much to do with one's preference:

1. What type(s) of analysis do you intend to run?

2. Is one software package available to you without cost (e.g., as a student, faculty, or employee of an organization that maintains a site license)?

3. Is one software package more familiar (because of prior experience) to you?

Without doubt, the fastest growing and most widely expanding list of general and specific analytic features (in terms of libraries being added each month) available in a "single" statistical software system is the open-source R package (https://cran.r-project.org/).

There is an spss work-alike program, PSPP, that is open-source. However, its list of analysis options is limited compared to those of SPSS (see link #1 below).

As well, there is a "free" path to using SAS, the SAS university edition, albeit with limited set of analysis options (see link #1, below).

Here are some helpful links to free / free to try general and specific statistical software packages that others might find useful:

1. https://www.predictiveanalyticstoday.com/top-free-statistical-software/

2. https://statpages.info/javasta2.html

Good luck with the popularity poll!

Mainly it depends on the field you’re in. Social scientists should generally learn SPSS as their main package, mainly because that is what their colleagues are using. You can then choose something else as a backup–either SAS, R, or Stata, based on availability and which makes most sense to you logically.

https://www.educba.com/spss-vs-sas/

Dear Layth Mhmood Yahya , between the two SPSS is more useful as more information and tweaks are available for SPSS. In addition to SPSS you must learn R and python.