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).
SAS is a very good product. SPSS provided our firm everythinbg we needed and was well within our budget. Also know that IBM is contunusely investing into SPSS. The roadmaps looks good.
Advanced statistical analysis is possible which is not possible in powerbi. It is very much easy to prepare basic charts. I dept statistical tests like regression analysis can be done. It is user -friendly and even layman can understand basic data easily through IBM SPSS's …
Data Scientist ,Pre-Sales,Consultor/Instrutor em Estatística e Mineração de dados em Big Data
Chose IBM SPSS Statistics
I also point out that the two softwares are complementary, then IBM SPSS Statistics works very well with statistical tests, creation and visualization of detailed tables and creation of statistical project models and project models. The IBM SPSS Modeler helps you quickly view …
Occupational Safety, Health, and Environment Technician
Chose IBM SPSS Statistics
I have also used other statistical software such as the SAP Predictive Analytics software, SAP possesses most of the decode options as SPS, but it is not as graphical and easier to use as SPS. Thus, IBM SPSS Statistics was chosen as a primary and powerful statistical tool that …
IBM SPSS Statistics stacks up much better and overall gives the user a much better as well as simpler means to achieve their end goal. It provides a comprehensive set of well tested data management, along with statistical procedures in an easy to use and all in one package …
We had not ever used anything as diverse as IBM SPSS Statistics before, so don't have much to compare it to but would highly recommend it based on all the previous comments before here. The platform is easy to use and again gives you a quick snapshot of company health based on …
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 …
We used IBM SPSS Statistics as it works well with the other IBM tools that we use. It may not work as well for smaller organizations with limited budget/resources. We have a mix of technical and devops people and this tool is easily used by everyone on the team globally.
I have on many occasions launched new versions of a big Python application in production, only to immediately drown in errors, caused by exceptions that were in turn caused by Python code where a single glance confirmed that it could never ever work and consequently had never …
IBM SPSS Statistics is much more professional and geared towards market research applications. The built in queries save time and avoid mistakes. In Excel you can also do powerful things, but it is less geared towards scientific or statistical research. Running a regression …
IBM SPSS Statistics is much easier to use, even in classes with students, compared to other similar data analytic software that I have used previously. I selected it because of this reason and I plan to continue using it in the future. The interface is user friendly and the …
I, along with my supervised research student, used IBM SPSS Statistics compared to other software because of its simplicity and user-friendliness. A timeframe is a fundamental part of research work. Time is precious for both of us in terms of research work and using IBM SPSS …
Verified User
Consultant
Chose IBM SPSS Statistics
The price of IBM SPSS and its quality-price ratio was one of the triggers for choosing the software over the competition. The ease of obtaining a demo of the product and the continuous training it presents was another of the key points in the decision making we made in the …
IBM SPSS Statistics Logistic Regression's user-friendly interface is among its most important benefits. Without the need for sophisticated technical knowledge, users can navigate and analyze their data with ease. As a faculty member of a university, I used it using its numerous …
Compared to Stata, python and MPlus, SPSS is more user friendly especially for beginners. It displays data and output in easily readable formats and makes statistics fun and easy. However, Stata, python and MPlus are more ideal for complex statistical methods like structural …
We tend to shy away from open source where possible. with SPSS from our feeder university system for our co-op interns, this is a great transition and a low barrier to getting them working quickly.
Deriving outcomes using the statistical analysis is the major advantage over all the above tools.
Verified User
Analyst
Chose IBM SPSS Statistics
For my own statistical analyses, I personally use R and MPlus. However, these tools have a steep learning curve and require dedicated time and a course on their own. In m yopinion, they are not useful for trying to quickly acclimate undergrads to the new world of stats and …
We have also analyzed and used products such as Minitab, R, Matlab, Q, Statistica, SAS and Stata. SPSS compares very well to them and has strengths and weaknesses just as any other analysis software. For our work environment, SPSS is the standard.
We actually use both Q Research Software and IBM SPSS. We started using Q [Research Software] about 5 years ago and initially thought it would replace [IBM] SPSS. While you technically can view .sav files directly in Q [Research Software], we found that the two softwares are …
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.
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.
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.
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.
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.
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.
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.