Hello Mochamad,

If you're asking, what software platform offers the widest and fastest-growing array of (freely available) quantitative tools, then there's no question: R (https://cran.r-project.org/).

For any given moment in time, the "best" processing tool choice would depend on: (a) the specific type(s) of analysis one intended to apply ; (b) cost; (c) ease of use; (d) correctness and robustness against challenging data sets; (e) how well documented the internal algorithms are; and (f) support for the tool.

In my experience, people often tend to reply to questions like this with whatever package they learned first. There is a very real learning curve associated with mastering any new statistical software.

That said, there's a lot of good packages from which to choose. Some of these (such as Jamovi & JASP) are built on R, with attempts to have a more "user-friendly" front-end. Other R front ends include R commander (https://socialsciences.mcmaster.ca/jfox/Misc/Rcmdr/), Deducer (https://www.deducer.org/pmwiki/index.php?n=Main.DeducerManual?from=Main.HomePage), R Studio (https://rstudio.com/products/rstudio/download/) and others.

Here's some additional links for either free (or free to try) quantitative analysis packages that you may find helpful:

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

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

3. (R libraries) https://cran.r-project.org/web/views/Psychometrics.html

Good luck with your work.

Thanks Mr David for your answer.

I agree with Dr Morse on R. It's IMO unbeatable. Get Jared Lander R for everyone available in the z-library and you can start running research grade code by using examples from the book. R runs on everything including smartphones. All of this is free. Best wishes, David Booth

Mochamad--

Honestly, the first stats package I learned was SPSS. While I still use it for some data management tasks (depending on the project and my role on it, the type of analyses, and the degree of familiarity with statistics of those I am working with), I find myself using STATA a lot more because I can do a lot more with it. My impression is that analysts tend to "outgrow" SPSS pretty quickly and need more-advanced software capacity.

That being said, many of my colleagues use R, as well. In my opinion, R definitely beats STATA in terms of being free and open source. It also offers data analytic longevity--no matter where you work or what you are working on, you won't lose access to R, so the skills you develop are a good investment.

However, from my experience, I think STATA and SAS have better documentation and support resources than R, especially considering some of the user-written R packages I have tried. But, I also recognize that I work at a university with a site license to STATA, so I have the luxury of choosing that program at no personal cost to me.

Hope this helps, and best of luck!

~Sarah

Depends what you mean by "processing." If you mean extracting data from a database, while I agree with the Davids (David Eugene Booth and David Morse ) that R is good for many things, and it has some tools for data processing / wrangling (see https://cran.r-project.org/web/views/Databases.html and https://www.amazon.com/Data-Wrangling-R-Use/dp/3319455982), it is also worth considering some variety of SQL. If you mean just what is a good stats package, delete this question and write one saying this.

Thank very much for all of the answers, inspiring and giving me a broader vision of statistical processing tools. I especially appreciate to Mrs Sarah for sharing experience and opinion of using stata and other processing tools.

Trims for all of the answers about processing software. Inspiring and enlarge my horizon.

there is a lot of software for quantitative research. but this is dependent on you what do you want to do? and what level do you want to work at?

Generally, I think Eviews for Time series and Stata for Panel data for usual quantitative research are enough. but R and Python are better for more advanced quantitative research.

Trims Mr Shahin for the answer. Very inspiring. Stata is somewhat difficult, but I am trying to learn it.