Worth doing the job right
Updated April 01, 2016

Worth doing the job right

Brian Harris | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Modules Used

  • IBM SPSS Statistics
  • AMOS

Overall Satisfaction with IBM SPSS

We use IBM SPSS frequently for analysis of survey data. The product is available to select individuals across departments, but mostly used by professional researchers. IBM SPSS is an industry standard so it's easily integrated with other software that exports or imports data, such as Qualtrics or Stata.
  • IBM SPSS generally creates nicer looking tables than other statistical software packages.
  • IBM SPSS is flexible for different kinds of users; it has easy to use drop-down menus for simple analysis as well as excellent coding reference help for more advanced procedures.
  • IBM SPSS is well-integrated with other software so that it's easy to import or export data from many different sources or file types. You can use SPSS to transform Stata, R, or SAS data into other file types without losing all your data labels, etc.
  • As with all statistical packages, the presentation of data is somewhat lacking. Although SPSS is better than many others, the tables don't export perfectly into Excel, and the graphs aren't nearly neat enough to present without major cosmetic adjustments.
  • IBM SPSS does not have a great process for saving post-analysis data. It can also be cumbersome to create new variables based on group means, etc.
  • Data analysis in IBM SPSS is faster than in Excel, especially when you need to create or transform a lot of variables. Recoding is much more efficient in IBM SPSS. This helps our clients get the end product much faster, and we can be confident in the results we present.
  • Stata and SAS
IBM SPSS is generally pretty comparable with Stata, except that Stata offers more niche analytical tools because of the active user community that adds new custom functions all the time. IBM SPSS syntax is much, much, easier to learn than R or SAS.
IBM SPSS is great for both academic and applied research settings. Anyone who has training in data analysis can learn to use the product fairly easily. Advanced users can use the syntax coding features (with excellent reference materials included in the help menu), and beginning users can easily navigate the user-friendly drop-down menus.


For people with research and coding backgrounds, it's easy enough to figure out on your own with some trial and error. For others, there are good tools in the help menu to walk new users through the processes step-by-step. Not all of the analyses are intuitive or easy to interpret, so you may have to use other online resources to help you use your results more effectively. Overall, it's not nearly as intimidating as other stats packages. I've seen a lot of people pick up basic SPSS skills relatively quickly with a little coaching from a mentor.
Like to use
Technical support not required
Well integrated
Feel confident using
Unnecessarily complex
Slow to learn
Lots to learn
  • Simple procedures like running crosstabs or frequencies are a piece of cake. They are easily modified and adjusted to output only the information you need, and it's easy to add a few extra little analyses to bring your data to life.
  • The color-coded syntax editor is really handy. It updates as you type to let you know if there are errors. This feature makes it easy to identify what the different segments of code do.
  • There are a lot of nice graph options within SPSS so you can visualize your data with a few clicks.
  • It's very easy to edit the data manually from the data editor view.
  • The output saves in a strange format that doesn't necessarily transfer well to a Word or Excel document.
  • The error messages you get when running syntax can be very cryptic and hard to decipher.