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
Microsoft Excel
Score 8.9 out of 10
N/A
Microsoft Excel is a spreadsheet application available as part of Microsoft 365 (Office 365), or standalone, in cloud-based and on-premise editions.
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 …
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 …
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 …
I also use or have used Tableau, Excel, and R (wasn’t able to list R above). Tableau is better for visualizations, Excel works for generalized/more basic statistical analysis but lacks more complex features, and R has been difficult for me to master and lacks the UI and ease of …
IBM SPSS Statistics beats the pants off of Minitab in every area except cost. Minitab has far cheaper entry-level costs, but the software is much more limited. With the versions of Minitab I have used, importing mapping data is a non-starter. With IBM SPSS Statistics, once the …
Out of Microsoft Excel, Microsoft Power BI, IBM SPSS, and Google Sheets, Microsoft Excel is by far the most common tool used for anything data-related across organizations. Accordingly, our organization has also implemented Microsoft Excel as a first-step tool. We recently …
Microsoft Excel is more functional for different purposes, such as also showing, filtering and sharing tables with text. Think of action lists, meeting minutes or spreadsheets with quantitative input. SPSS is more focused on statistical analysis, performing built in analysis, …
It isn't as collaborative or detail oriented as other platforms, or at least it doesn't market itself to be used that way. But it is still useful in its own ways
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.
I don't really know another program as powerful as Excel. I've used Google Doc programs but do not feel they come close. So far, anytime I've needed a table of some sort for data, whether it's budget oriented or information off a survey, the best system has been Excel. We do web audits on occasion and we create an Excel worksheet featuring every URL of the pages we're auditing, notes, data about the content, information about files attached to the page and other information to help us determine what pages need updating, deleting or otherwise. We also use Excel primarily to export our Google Analytics to in order for us to create reports for clients that need to see specific information about their traffic.
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.
It is very good at embedded formulas and tying cells to one another
It allows me to compare deals terms on a side-by-side basis and talk my clients through it easily.
It is very helpful as well in terms of allowing me to filter/sort results in many different ways depending on what specific information I am most interested in prioritizing.
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.
Excel offers collaboration features that allow multiple users to work on the same spreadsheet, but managing changes made by different users can be challenging. Excel could improve its features by offering more granular control, better tracking of changes, and more robust conflict resolution tools.
Itcan be a barrier to productivity when importing and exporting data from other applications or file formats. To improve its features, it should offer better support for standard file formats and more robust error handling and reporting tools.
Excel can be challenging for finance students and working professionals, but it can be improved by offering more robust tutorials, better documentation, and more user communities and support forums.
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
Excel remains the industry standard for spreadsheets and has maintained simple and straight-forward formula writing methods. Although there is a learning curve to do more complex calculations, there are countless help sites and videos on the Internet for almost any need.
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'm giving it a 7 because it is my go to. But the fact other prefer Google Sheets when working with a team does get irritating. I've used the online version of Microsoft Excel that other teams can get into and it still seems behind Google Sheets. It's a little clanky and slow? If that's even a term.
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.
Out of Microsoft Excel, Microsoft Power BI, IBM SPSS, and Google Sheets, Microsoft Excel is by far the most common tool used for anything data-related across organizations. Accordingly, our organization has also implemented Microsoft Excel as a first-step tool. We recently adopted Microsoft Power BI (the free version), and use it occasionally (mostly for creating dashboards), but it is less commonly understood by stakeholders across our organization and by our clients. Accordingly, Microsoft Excel is more user-friendly and because of its popularity, we can easily look up how to do things in the program online. Google Sheets is a comparable alternative to Microsoft Excel, but because it's cloud-based and we have sensitive data that needs to be protected, we chose against using this software. Finally, a few users (including myself) have access to and utilize IBM's SPSS. For my role, it's a helpful tool to do more rigorous analyses. However, because of its cost and limited functionality as a simple spreadsheet, we only use it for more complex analyses.
Each user can use it to whatever level of expertise they have. It remains the same so users can contribute to another's work regardless of whether they have more or less expertise
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.
