R and SPSS difference

Question

I will be analysing vast amount of network traffic related data shortly, and will pre-process the data in order to analyse it. I have found that R and SPSS are among the most po

Answer 1

I work with both in a company and can say the following:

• If you have a large team of different people (not all data scientists), SPSS is useful because it is plain (relatively) to understand. For example, if users are going to run a model to get an output (sales estimates, etc), SPSS is clear and easy to use.

That said, I find R better in almost every other sense:

• R is faster (although, sometimes debatable)
• As stated previously, the syntax in SPSS is aweful (I can't stress this enough). On the other hand, R can be painful to learn, but there are tons of resources online and in the end it pays much more because of the different things you can do.
• Again, like everyone else says, the sky is the limit with R. Tons of packages, resources and more importantly: indepedence to do as you please. In my organization we have some very high level functions that get a lot done. The hard part is creating them once, but then they perform complicated tasks that SPSS would tangle in a never ending web of canvas. This is specially true for things like loops.

It is often overlooked, but R also has plenty of features to cooperate between teams (github integration with RStudio, and easy package building with devtools).

Actually, if everyone in your organization knows R, all you need is to maintain a basic package on github to share everything. This of course is not the norm, which is why I think SPSS, although a worst product, still has a market.