I’ve already read a few dozens of articles on how does the statistical software (such as R) is different from the SPSS? Both are meant to work with data, yet some say R is more suitable for working with bigger data samples (as compared to SPSS). I aim to ask experts in order to get more info on the topic of pros (as well as shortcomings) of using R
R does things that SPSS never imagined a nd does them correctly. See variable selection models for example. Discussed in the attached. Best , D. Booth
R does things that SPSS never imagined a nd does them correctly. See variable selection models for example. Discussed in the attached. Best , D. Booth
What do you consider "bigger data"? And what kind of analyses do you want to conduct?
Hello Iryna,
I would suggest having both of them in your skills, and use them according to the analysis you are going to conduct. While SPSS is much easier to use, R is much more powerful for many analyses.
Good luck with your work!
As others have said, the major advantage of R is the enormous flexibility for handling different kinds of data and performing virtually any kind of analysis one wishes. However, SPSS is much more intuitive and user-friendly. There is very little coding required in SPSS. R, on the other hand, is essentially all coding. Thus, there is a much flatter learning curve for R - particularly for individuals with little coding experience. Conducting analyses in SPSS can be learned relatively quickly.
Plotting curves like violin plot and dot plots can be done effectively in R.But R is far more complex in managing the script unlike SPSS.But the flexibility of packages in R is unmatchable.
The only seemingly shortcoming of R over SPSS is your ability to use it because of a lot of coding required in its usage. For its pros over SPSS, its flexibility is indeed unmatchable, even statistical tools that are yet to be developed has space in R.
Talking from my personal experiences with my data, if you are thinking about publishing in a high impact journal better you consider Python even more over R. Making colourful and presentable plots are far easier and prettier in Python than even R. SPSS makes few of the most unimpressive graphs possible. I think excel statistical add ins make it a potent force as well.
If you don't like coding try Rcommander,, SPSS with more power and ease. see:
https://www.google.com/search?q=r+commander+tutorial&rlz=1C1CHBF_enUS917US917&oq=RCommander&aqs=chrome.6.69i57j0l7.24337j0j1&sourceid=chrome&ie=UTF-8
According to me in R you can make your customized programs. for programmer or anyone have some knowledge of programming I can recommend R.
Keep knowledge over both R and SPSS. Use them according to your objective/ need.
Is that even a valid question? R is absolute in the field. If you absolutely dislike the idea of coding and don't want to learn a programming language, then you will be set with an IDE, like Jamovi or Rcommander.
Jamovi is a fascinating project. Give it a try.
https://www.jamovi.org/
Igor Eloi and please do not forget JASP, which is very similar to JAMOVI, with much more built in methods, but with less freedom to install external procedures.
Dear Rainer thnk you for indicating JASP, the result of JASP have a good look and are consistent of APA format.
SPSS stands for Statistical Package for Social Sciences
If you are in Social Sciences, SPSS is for you
Sergio Ibarra-Espinosa so if I am not a social scientist I am not allowed to use SPSS and vice verca, social scientists should not use R oder other programs?
Rainer Duesing You are free to do anything. However, there are some products designed for a target audience.
I would say R can do everything SPSS can. So what do you mean by designed for. And btw:"The software name originally stood for Statistical Package for the Social Sciences (SPSS),[2] reflecting the original market, then later changed to Statistical Product and Service Solutions"
Hi Iryna E. Zelinska
It depends on your data, money and time to learn.
SPSS is an amazing tool, if you can buy it, and you data fits the requirement of the tool, perfect, go with it.
If you have a big data, database, binary data (HDF, NETCDF), I would go with R or Python. These tools are free and they can handle this type of data pretty well. You just need to stop and learn how to use them and develop your own code to process and analyze your data.
Regars
R is flexible and it is easier to understand. Besides, the software, the packages, and most times, the codes are free online.
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