
I’ve been using IBM SPSS for a while now, mainly for statistical analysis and research projects, and overall it’s a solid tool with a few caveats. On the positive side, the biggest strength of SPSS is that it makes complex statistical analysis far more approachable. The interface is much more user-friendly compared to coding-heavy tools like R or Python, especially for people who aren’t from a hardcore programming background. Running regressions, factor analysis, ANOVA, or even advanced tests becomes very straightforward with the menus and options. The output tables and charts are also clean, easy to export, and presentation-ready, which saves a lot of time. Review collected by and hosted on G2.com.
That being said, SPSS does feel a bit dated in some areas. The interface hasn’t evolved much over the years, and sometimes it feels clunky compared to newer platforms. It’s also not the best when it comes to handling really large datasets, performance can get slow. Another downside is the cost. For students it’s manageable with discounted licenses, but for professionals or small organizations, the pricing is quite steep compared to free alternatives like R or Python, which are more flexible if you’re willing to put in the effort to learn coding. Review collected by and hosted on G2.com.
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