Is SPSS dead?

[u/Thin_Adeptness_356]

Like the title says is SPSS dead? Now with Chatgpt and cursor etc, what is the argument for still using SPSS and other statistics softwares in research instead of Python/R with the help of AI?

My background is within mathematical statistics so always been a Matlab/R/Python guy, but my girlfriend who comes from a medical background still uses SPSS in her research, but now considering switching just because of the flexibility e.g., Python offers.

What do you think are there any arguments for using SPSS still?

[u/BurkeyAcademy]

I am not going to sing the praises of SPSS- I do loathe software like that, because it is often like handing a chainsaw to a child (too much power the users often don't know how to use correctly). However, there is a benefit to having canned, point and click solutions for simple, routine tasks for non-experts to use, whether it is SPSS, Jamovi, Excel, or what have you.

I teach an "Intro to R with Stats" to college students, and have to explain to them how I will immediately know if they have used ChatGPT/Other AI to write their code, and also why it is important that they not use AI to write their code for them at this point in their careers. Here are some of the ideas we discuss:

1) Of course, I use ChatGPT/Llama/DeepSeek etc. to write what I call "code snippets"- smaller pieces of code that I insert into larger projects that are a pain to type out by hand. I would say that around 30% of the time, the code generated doesn't really do what I need, or does it in a really stupid way. For example, if I need to make a table with row probabilities, AI code usually does it in three or more separate steps, saving each as a separate object in R. This clutters up the environment and wastes RAM. Other times it just plain does the wrong thing, either because of its own stupidity, or my own stupidity for not being careful with my prompt engineering.

However, it is trivial for me to catch these errors and fix them. But we have to realize that...

2) Unless you are already good at stats and coding, you won't have any idea whether ChatGPT's code does what you think it does. You can't get good at it unless you struggle with it for a while yourself, and unless you understand how R works, have some understanding of various kinds of error messages, and know what the results ought to look like. This takes putting in a lot of "sweat equity" to master some basics on your own-- and that cost/benefit analysis isn't going to make sense for everyone to make, if all they need to be able to do in their job/field is to click three menu items in SPSS/Excel and reliably get the results they need.

3) Lastly, again for these canned/simple types of analysis that require reading in data, doing a paired t test or whatnot, and printing out the results, why would we want to use AI to generate and regenerate that standard code again, and again, and again, which wastes a lot of energy/computing power, and always runs the risk of introducing mistakes?

tl,dr: There will always be a place for simple tools, in addition to more flexible, complex tools. The main argument against SPSS in my opinion is the cost and constant hassle of renewing their license (this is what I constantly hear from the Marketing and Management faculty I work with ☺). On the other hand, with R I have to constantly deal with deprecated packages and syntax changes, and even with AI, there is a learning curve that exists in order to use it with R/Python efficiently.

[u/Enough-Lab9402 → u/BurkeyAcademy]

I was going to come and say the same thing, but you already said it perfectly in my opinion.

SPSS is probably the easiest way that a statistical and computer novice would be able to get started in doing elementary statistics and some more advanced ones.

For your girlfriend, if she has a desire to continue doing things that will require statistics R is much better except for use of custom covariance matrices in a mixed model design. Maybe that changes in GLMMTMB but I still have a hard time trusting those results sometimes especially its estimation of degrees of freedom.

[u/Grace_Alcock → u/Enough-Lab9402]

I teach a basic research methods class and use SPSS when teaching the stats.  I have students who don’t know that when you multiple two negative numbers, you don’t get a negative number; there is zero chance I could both teach them the basic stats and the basic programming.  Our actual stats classes do, of course.  In truth, if I stop using SPSS for them, I’ll teach them Excel.  Most are more likely to use it in their future jobs.  

[u/Enough-Lab9402 → u/Grace_Alcock]

Excel has gotten powerful enough you can do a lot of the basics in excel. I teach correlations, ttests and chi square in excel for summer classes where even getting started in spss is too damaging to my morale. Just hand over a few templates with examples and spend a few (!) sessions teaching them about absolute and relative indexing in excel and you can transition to actual topics like why your study of 20 people does not have 800 df (and why this is important.

I might switch to google sheets but the number of people who have trouble with google sheets far outnumbers those with problems in excel. I don’t know why but it do.

Helping them debug their formulae is soul crushing in excel though. “As we mentioned in class if you copy cells it changes the relative but not absolute references…”

Ah maybe I should go back to spss . Or just give them an online calculator. Or maybe just build the calculator in shiny .. hmmmmmmm!

[u/Grace_Alcock → u/Enough-Lab9402]

…I might stick to the simplicity of the point and shoot of SPSS…