I'll start with an admission: I detest SPSS. However, this is mostly because I am required to teach it to students who can then use it to use methods they don't really understand to get answers from data they can't interpret. In other words, SPSS is seemingly designed to enable one to use statistical techniques, methods, etc., one doesn't understand. In fairness, this doesn't mean that one who does understand them can't use SPSS. In particular, everything one can do with R one can do with SPSS because current versions of SPSS can be enabled to utilize R. However, SPSS also offers a VASTLY easier, more intuitive, and generally superior interface than R. This is its blessing and its curse. SPSS is generally used by those who never use go beyond the button-pushing approach- they don't customize or do so minimally, they treat SPSS as a kind of sophisticated Excel (which it resembles for a reason), and they are unable to utilize the more advanced capabilities of SPSS. The SPSS interface makes this possible, but it is not required.

There are a lot of freeware interfaces available for the R user, from RExcel to Rcommander. SPSS, though, is in some sense one of these, but it offers a vastly superior interface for using statistical methods independently of R when the level of customization R can obtain is unnecessary.

SPSS has features you can't get from R, because R is freeware and no R GUI, R interface, or incorporation of R within some larger free software package can offer what SPSS does. SPSS can make much simpler numerous standard statistical measures/tests that require coding if one uses R. This ease comes at a price: it is possible to feed data into SPSS and get results that are garbage without being able to know what is garbage and why. It's harder to do this with R.

In short, there is nothing SPSS can do which R can't, but there are a vast number of things it can do with much greater ease. This ease comes at the potential price of being able to us lots of methods/measures/tests one doesn't understand, but this is again only a potential. Also, customizing one's approach is basically a must with R, while it is much harder with SPSS.

R is superior in general. That doesn't make it the better choice. SPSS can be just as good, but it is vital to ensure that it isn't used as a crutch.

Hi Sujeet

Both apps are equivalently good. But in my opinion, graphically SPSS is better. Money-wise in the long run, I personally tends to side on R.

I agree with Saiyidi. R lets you do more than SPSS at the higher levels of statistical analysis, but I think SPSS is easier to use and to teach as well as being better for graphics.

Dear Dr. Sujeet

softwares have its own limitations, what exactly you are going to solve using these software will help you better to decide which one you should use. I may say R is used for hardcore statistical stuff than SPSS, which is very specific even mapple and pc give can help you. How many licenses you are looking, is it used for teaching or for individual research, there are many more factors that counts while deciding which one is better.

SPSS is very much light in view of application and user friendly. You can design the data shape in any format you want through SPSS. Here you can compile larger files with excel or IMS data. Whereas R is more complex in functioning and you must have a profound syntax skill in data processing with R. That's why I"ll vote for SPSS for business analysis.

R is free...

There is a very user-friendly package called Rmdr

you should install R and run this lines;

install.packages("Rcmdr", dependencies=T)

once installed you can called it using this line in the console:

library(Rcmdr)

You'll have a user interphase very similar to that you get with SPSS:

try it... and I insist, it is FREE!

Thanks everyone for useful information.

I'll start with an admission: I detest SPSS. However, this is mostly because I am required to teach it to students who can then use it to use methods they don't really understand to get answers from data they can't interpret. In other words, SPSS is seemingly designed to enable one to use statistical techniques, methods, etc., one doesn't understand. In fairness, this doesn't mean that one who does understand them can't use SPSS. In particular, everything one can do with R one can do with SPSS because current versions of SPSS can be enabled to utilize R. However, SPSS also offers a VASTLY easier, more intuitive, and generally superior interface than R. This is its blessing and its curse. SPSS is generally used by those who never use go beyond the button-pushing approach- they don't customize or do so minimally, they treat SPSS as a kind of sophisticated Excel (which it resembles for a reason), and they are unable to utilize the more advanced capabilities of SPSS. The SPSS interface makes this possible, but it is not required.

There are a lot of freeware interfaces available for the R user, from RExcel to Rcommander. SPSS, though, is in some sense one of these, but it offers a vastly superior interface for using statistical methods independently of R when the level of customization R can obtain is unnecessary.

SPSS has features you can't get from R, because R is freeware and no R GUI, R interface, or incorporation of R within some larger free software package can offer what SPSS does. SPSS can make much simpler numerous standard statistical measures/tests that require coding if one uses R. This ease comes at a price: it is possible to feed data into SPSS and get results that are garbage without being able to know what is garbage and why. It's harder to do this with R.

In short, there is nothing SPSS can do which R can't, but there are a vast number of things it can do with much greater ease. This ease comes at the potential price of being able to us lots of methods/measures/tests one doesn't understand, but this is again only a potential. Also, customizing one's approach is basically a must with R, while it is much harder with SPSS.

R is superior in general. That doesn't make it the better choice. SPSS can be just as good, but it is vital to ensure that it isn't used as a crutch.

I mostly agree with Andrew Messing: SPSS offers a more user friendly experience than R but the main point here is, in my opinion, who is going to use the software and the reports produced with it?

If you want to do business in the sense that you need statistical analyses of e.g. customer satisfaction data, you have some knowledge of statistics and will present the results/interpretations, I would use R. You will be able to use cutting-edge methods and algorithms that have been validated by thousands of scientists. This is the reason why an increasing number of (possibly big) companies are starting to rely on R and hire statisticians for that purpose.

If you for "doing business" you mean that the analyses/results are to be read/repeated also by managers with little to no knowledge of statistics and your focus is on quality of reporting surrounded by sound statistical method (but without being sure about correctness of all results) then I would choose SPSS.

The added value of SPSS for me is that if you own a business and one day something goes wrong, you might want to have someone to blame and to fix it, and if this one is an external software company then in some sense "it's not your fault", whereas if the problem has to be fixed by the statistician/computer scientist working for the company is more onerous.

Hi Sharma

1. There are many similarities between Statistical Software Packages (SPSS, SAS, R, Stata, JMP, …) in the logic and wording they use even if the interface is different.

2. Many schools offer only a site license for only one package, and it may not be the one you’re used to.

3. Statisticians, social scientists, … should generally learn SPSS as their main package, mainly because that is what their colleagues are using.

4. SPSS is used by market researchers, health researchers, survey companies, government entities, education researchers, marketing organizations, data miners, and many more for the processing and analyzing of survey data.

5. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next.

Regards,

Zuhair

This is a very useful infographic by the Datacamp team in 2014

https://www.datacamp.com/community/tutorials/statistical-language-wars-the-infograph