SPSS Statistics is a software package used for statistical analysis. It is now officially named "IBM SPSS Statistics". Companion products in the same family are used for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS Modeler), text analytics, and collaboration and deployment (batch and automated scoring services).
$105
per month per user
JMP Pro
Score 6.0 out of 10
N/A
JMP Pro offers all the capabilities of JMP, plus advanced features for more sophisticated analysis including predictive modeling and cross-validation techniques.
Stacks up pretty well, as this is the best geospatial analysis tool next only to ArcGIS, but does almost everything that other packages do almost as well. However, there is a considerable need to improve and include new techniques like the random forest, etc. which IBM SPSS …
JMP is user-friendly like SPSS but is more limited in terms of data analyses.
SAS is better for managing and modifying large datasets. SAS also provides more customization for analyzing things like group differences. However, SAS does not handle modifying string responses well. …
IBM SPSS Statistics is well suited for pretty much any data analytic scenario. It can handle extremely complex and large-scale datasets with ease. It especially shines if you have to do any kind of analyses that involve significance testing. Being able to do any number of significance tests (i.e., t-tests, chi-square, ANOVAs, etc.) right inside the tool is very valuable. The only scenario I would say it is less appropriate is if you need to work on a very small dataset and answer very simple questions, like frequencies or averages. In those cases, something like Excel could probably do the job just as easily.
JMP Pro is perfectly suited for statistical analysis but users should have some statistical knowledge before using it since there may be some terms/functions in the software that are not widely used in other fields. No prior coding experience is needed to use JMP Pro. However, most people doing data processing would prefer to code their analysis.
SPSS has been around for quite a while and has amassed a large suite of functionality. One of its longest-running features is the ability to automate SPSS via scripting, AKA "syntax." There is a very large community of practice on the internet who can help newbies to quickly scale up their automation abilities with SPSS. And SPSS allows users to save syntax scripting directly from GUI wizards and configuration windows, which can be a real life-saver if one is not an experienced coder.
Many statistics package users are doing scientific research with an eye to publish reproducible results. SPSS allows you to save datasets and syntax scripting in a common format, facilitating attempts by peer reviewers and other researchers to quickly and easily attempt to reproduce your results. It's very portable!
SPSS has both legacy and modern visualization suites baked into the base software, giving users an easily mountable learning curve when it comes to outputting charts and graphs. It's very easy to start with a canned look and feel of an exported chart, and then you can tweak a saved copy to change just about everything, from colors, legends, and axis scaling, to orientation, labels, and grid lines. And when you've got a chart or graph set up the way you like, you can export it as an image file, or create a template syntax to apply to new visualizations going forward.
SPSS makes it easy for even beginner-level users to create statistical coding fields to support multidimensional analysis, ensuring that you never need to destructively modify your dataset.
In closing, SPSS's long and successful tenure ensures that just about any question a new user may have about it can be answered with a modicum of Google-fu. There are even several fully-fledged tutorial websites out there for newbie perusal.
Availability of procedures in the base package seems to be dwindling.
The copy-and-paste function from output to Excel is not as easy as it once was (now I have to do a "paste special").
Text and date handling are terrible.
Need to include AI-based NLP for survey verbatims and other text-based fields. This is becoming increasingly important in the CX world, yet SPSS seems to be ignoring it.
JMP Pro is a really powerful tool for doing statistical analysis. Although the click environment does not require coding experience, new learners will still need to take a long time to know the parameters in the function before performing any analysis.
The output from JMP Pro analysis (regression analysis) is not always easy to understand, especially when the parameters are programmed differently with the other similar software.
Both money and time are essential for success in terms of return on investment for any kind of research based project work. Using a Likert-scale questionnaire is very easy for data entry and analysis using IBM SPSS. With the help of IBM SPSS, I found very fast and reliable data entry and data analysis for my research. Output from SPSS is very easy to interpret for data analysis and findings
Probably because I have been using it for so long that I have used all of the modules, or at least almost all of the modules, and the way SPSS works is second nature to me, like fish to swimming.
JMP Pro is a great tool, but it's not user friendly. JMP Pro is something that requires a lot of trial and error to figure out. Minitab is far more user friendly and their help guides walk new users how to do everything. JMP Pro requires taking the time to do the STIPs course, or brute force figuring it out.
I have not contacted IBM SPSS for support myself. However, our IT staff has for trying to get SPSS Text Analytics Module to work. The issue was never resolved, but I'm not sure if it was on the IT's end or on SPSS's end
Have a plan for managing the yearly upgrade cycle. Most users work in the desktop version, so there needs to be a mechanism for either pushing out new versions of the software or a key manager to deal with updated licensing keys. If you have a lot of users this needs to be planned for in advance.
If you have made it this far, you should have a very good idea of how SPSS stacks up the competition (data processing and analytics tools). Even the free ones, such as r Studio or Stata, are leaps and bounds ahead of SPSS. IBM is resting on a reputation developed nearly 30 years ago and has shown no desire to improve.
I use both JMP Pro and Minitab. JMP Pro works great for doing the work that needs live edit functionable, and the ability to filter charts on the go. Minitab is what I use for capability analysis and MSAs as the overall UI is much cleaner, and is far nicer to present to management than JMP Pro.
I found SPSS easier to use than SAS as it's more intuitive to me.
The learning curve to use SPSS is less compared to SAS.
I used SAS, to a much lesser extent than SPSS. However, it seems that SAS may be more suitable for users who understand programming. With SPSS, users can perform many statistical tests without the need to know programming.
