IBM SPSS Statistics vs. JMP Pro

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Statistics
Score 8.2 out of 10
N/A
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).
$99
per month per user
JMP Pro
Score 8.1 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.N/A
Pricing
IBM SPSS StatisticsJMP Pro
Editions & Modules
Base
USD 3,830
one-time fee per user
Standard
USD 8,440
one-time fee per user
Professional
USD 16,900
one-time fee per user
Premium
USD 25,200
one-time fee per user
Monthly subscription
USD 99
per month per user
Annual subscription
USD 1,188.00
per year per user
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS StatisticsJMP Pro
Free Trial
YesNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
IBM SPSS StatisticsJMP Pro
Considered Both Products
IBM SPSS Statistics
Chose IBM SPSS Statistics
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 …
Chose IBM SPSS Statistics
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. …
JMP Pro
Chose JMP Pro
It's much more user-friendly and has a wider statistical toolset.
Best Alternatives
IBM SPSS StatisticsJMP Pro
Small Businesses

No answers on this topic

IBM SPSS Statistics
IBM SPSS Statistics
Score 8.2 out of 10
Medium-sized Companies
Alteryx Platform
Alteryx Platform
Score 9.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Alteryx Platform
Alteryx Platform
Score 9.0 out of 10
Posit
Posit
Score 10.0 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
IBM SPSS StatisticsJMP Pro
Likelihood to Recommend
6.9
(103 ratings)
9.0
(2 ratings)
Likelihood to Renew
8.6
(23 ratings)
-
(0 ratings)
Usability
8.0
(15 ratings)
-
(0 ratings)
Availability
6.0
(1 ratings)
-
(0 ratings)
Performance
6.0
(1 ratings)
-
(0 ratings)
Support Rating
6.4
(12 ratings)
-
(0 ratings)
Implementation Rating
8.7
(7 ratings)
-
(0 ratings)
Configurability
5.0
(1 ratings)
-
(0 ratings)
Ease of integration
5.0
(1 ratings)
-
(0 ratings)
Product Scalability
5.0
(1 ratings)
-
(0 ratings)
Vendor post-sale
5.0
(1 ratings)
-
(0 ratings)
Vendor pre-sale
5.0
(1 ratings)
-
(0 ratings)
User Testimonials
IBM SPSS StatisticsJMP Pro
Likelihood to Recommend
IBM
I described earlier that the only scenarios where I use SPSS are those where we have legacy projects that were developed in the late 90s or early 2000s using SPSS, and for some reason, the project (data set, scope, etc.) hasn't changed in 24+ years. This counts for 1-2 out of around 80 projects that I run. Whenever possible, I actively have my team move away from SPSS, even when that process is painful.
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JMP
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.
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Pros
IBM
  • 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.
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JMP
  • Several types of segmentation models
  • Conjoint design
  • VERY user-friendly
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Cons
IBM
  • collaboration - SPSS lacks collaboration features which makes it near impossible to collaborate with my team on analysis. We have to send files back and forth, which is tedious.
  • integration - I wish SPSS had integration capabilities with some of the other tools that I use (e.g., Airtable, Figma, etc.)
  • user interface - this could definitely be modernized. In my experience, the UI is clunky and feels dated, which can negatively impact my experience using the tool.
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JMP
  • 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.
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Likelihood to Renew
IBM
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
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JMP
No answers on this topic
Usability
IBM
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.
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JMP
No answers on this topic
Reliability and Availability
IBM
SPSS can tend to crash when I am trying to do a lot of data. This can slow me down when I need to do a lot of data
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JMP
No answers on this topic
Performance
IBM
SPSS does the job, but it can be slow. I do have to plan a lot of time to get through a huge amount of data.
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JMP
No answers on this topic
Support Rating
IBM
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
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JMP
No answers on this topic
Implementation Rating
IBM
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.
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JMP
No answers on this topic
Alternatives Considered
IBM
I have used R when I didn't have access to SPSS. It takes me longer because I'm terrible at syntax but it is powerful and it can be enjoyable to only have to wrestle with syntax and not a difficult UI.
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JMP
It's much more user-friendly and has a wider statistical toolset.
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Scalability
IBM
I am neutral because I have not had to look into scalability since I am using as a student.
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JMP
No answers on this topic
Return on Investment
IBM
  • 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.
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JMP
  • It helped me put together meteorological data from different locations to show which area is the optimal location for wind energy.
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ScreenShots

IBM SPSS Statistics Screenshots

Screenshot of SPSS Statistics Forecasting. This enables users to build time-series forecasts regardless of their skill level.Screenshot of SPSS Statistics Regression. These predict categorical outcomes and apply nonlinear regression procedures.Screenshot of IBM SPSS Statistics Neural Networks. These can discover complex relationships and improve predictive models.Screenshot of IBM SPSS Statistics Curated Help. These can interpret correlation output.Screenshot of IBM SPSS Statistics AI Output Assistant interprets statistical output in easy to consume language