IBM SPSS Statistics Reviews

I have wide experience with SPSS Statistics. I have even written books about it.  

Statistics is part of analysis, but SPSS Statistics has some differences from just straight analysis. It is also a modeler, has some automation, and can build models like linear regression. It is completely different when you use a modeler for your analysis. A modeler is designed specifically for building models of data in an automated way and using the models for prediction, and forecasting. It can help you see the data and the meaning in different ways.  

Because I am a statistician, originally I am trained for both modeling and non-parametric analysis. Most modeling tools are completely different. They have no non-parametric analysis because they are used for large sample data or big data analysis.  

The primary use for SPSS Statistics for me is, of course, data analysis.  

IBM SPSS Modeler is a set of data mining tools that enable us to develop predictive models. It has both statistical techniques (like regression techniques) or non statistical techniques (like Classification trees , Neural networks etc.). It doesn’t contain mainly the Nonparametric tests, may be because it depends on small samples.

It has automation nodes that helps non-experts to pick the best technique.

On the other hand, IBM SPSS Statistics is used mainly to analyze data, weather it is a small or large sample. If it is small (and drawn from non-normal population), then we must use the non-parametric tests. It has “automated” non-parametric tests to be use by both experts and non-experts.

Beside its main use for data analysis, it has also some modeling techniques like automatic linear modeling, Classification trees and Neural networks.

This product provides the opportunity to better explore data and provide complete data analysis because it works both with modeling and non-parametric analysis.  

I like SPSS too much to want to make changes to the product in a major way. There are some minor things. The one thing I can think of that will be useful in a broader sense is that it may be nice to be able to add color to some of the data in sheets or reports. Sometimes it is easier for you to visualize results if you can use color inside the datasheets.  

The original concern or intent of products like this is to analyze data, not to manipulate the data. But there are times when you need to manipulate data. This is something that would help more in data entry because there should be ways to fix errors in manual entry, et cetera. Addition of some data manipulation capabilities may be good for some things, but often you would do that outside of SPSS as it is not the purpose of the tool.  

SPSS Statistics will be more efficient if it starts to use additional automation. The advantage of automation in SPSS automation is obvious and exemplified in regards to the modeler, the non-parametrics, and the linear regression. But if they can add more automation in other areas, I think it will be more powerful. For example, the data science can have additional automation, for serious data science or something like EMA (Ecological Momentary Assessments). This would be a very interesting addition to SPSS Statistics.  

They can also add some automation with regression itself. Like logistic regression and alternate regression. Some people do not know the difference between binary, logistic, and the multinomial logistic analysis. It is an advantage in the SPSS Modeler. It is automatic. It can detect what type of modeling to choose. If a part of the variable is binary, it will use binary logistics. If it is appropriate it will use multiple logistic regression. It can detect this and do it automatically.

So, if SPSS Statistics starts to use some additional automation, it will be a step between the statistics and more serious data science. Those powers would be remarkable. Data science currently is the future in my estimation. More of the world of business and finance and other areas are starting to think about the applications of data science. And data science needs some data engineering, which is possible to realize through automation. This is especially true in some things like data tracing.  

If they take those steps to add some automation to the SPSS Statistics, it will push more people to understand the importance of analytics and advanced data science.  

But if it can achieve automation, I believe that SPSS Statistics has to do more within the application and the company to stress the importance of learning statistics before learning SPSS itself. If SPSS can add in its development or integration some short notes about how to use statistics, that would help users. It is not enough to be able to push buttons to get an analysis. This would give you a result that you will not understnd.  

SPSS could include an advantage of statistical analysis that goes beyond just the analysis itself. For instance, if you pick to do a logistic regression, you would find a short note about what logistical evaluation is and then how to use it within SPSS. It should not be integrated with the menu itself. It should be inside the statistical analysis area. Most of the people using the SPSS Statistic know which modeling they should use. But it is not always the case. It could be more of a learning tool as well as a productive one.  

A few years ago, SPSS made something that could be useful. It is called the Statistical Coach. It asks you some questions, and based on your answer, the coach guides you as to what to use. It was a good statistical coach. But if they can summarize the most important tests, I believe it is not too hard to make something that would be very useful inside the application and modeler itself.  

If you have the experience with data science, you will know how to do what you want to do using different tools — even competing products with SPSS. I can understand if somebody has to ask me how to do two-way ANOVA in SPSS, for example, as it is not an obvious thing. I will guide him through that if they needed to do it. SPSS can clarify how to do things in their application especially analysis that is common usage. In a way, the tool itself could provide more training for the people using it.  

I have been working with IBM SPSS (Statistical Package for the Social Sciences) since its name was Clementine. I think that was version 11. Now it is version 18. I think I have been working with it for eight years approximately.  

I have not used the IBM technical support for SPSS Statistics directly. I am working with SPSS since version eight back in the eighties or early nineties. So it is now version 27 and I have been working with the product for 20 versions. I have become very familiar with this product and all its changes over that period of time. Because of that, it is not necessary for me to contact the customer support.  

I believe that the initial setup is simple. The problem of SPSS Statistics, it is not to click the icon to do the installation. The problem of Statistics is to know which statistical analysis you have to use.  

Some people used to say that they know how to use SPSS Statistics, but they do not know which type of analysis to use. The manufacturer of the tool may want to do something to include training in the initial setup so that the users know more about the tool that they are using.  

In comparing the price of other products, SPSS Statistics is too expensive. Even when most of the universities in the Middle East have licenses for SPSS Statistics, they do not have licenses for the Modeler because of its price. This reduces the utility of the product.  

I have had the opportunity to evaluate some tools. The differences are not always obvious in casual use.  

For example, there are some little differences between SPSS and Minitab. If you want to make something called two-way ANOVA (Analysis of Variance), you can find it directly, and clearly in the Minitab interface. It is right in the menu and you can pick two-way ANOVA. But if you are thinking of two-way ANOVA using SPSS, you will not find it. You will find only one-way ANOVA. To make two-way ANOVA, you have to go to the general linear model, pick the univariate to use to obtain the two-way ANOVA. It is there and done a different way, it is just not called a two-way ANOVA. It is known as general linear model. The only problem is that the type of analysis is not known as two-way ANOVA in SPSS.  

So the difference is not that this type of analysis is impossible in one product and not the other.  

On a scale from one to ten where one is the worst and ten is the best, I would rate IBM SPSS Statistics between eight and nine. If they add some automation with time series and regression analysis exactly as they did with the linear regression, it would be a much better tool. If you open the regression modeling, the first item you will find is an automatic linear model. It uses the best technique, which is either is forward analysis or is stepwise. It can anticipate the user's needs and train at the same time. Some additional capabilities of this sort will push the tool forward as well as empowering the users.  

We primarily use the solution for analytics. 

The analytics on offer are very good.

It offers very good visualization. 

The dashboards are excellent. 

It's stable. 

The reports could be better. Usually, when we make reports, we use Microsoft of PowerPoint. Editing in PowerPoint is not so easy. You should be able to edit things a bit more. We can't edit the graphs or tables. It does auto-sync there. If I change something in Excel, it will be reflected in Word. The same should be possible with this solution. 

We'd like more engagement and advice. We need more integrations to help make analysis more powerful. 

The pricing is a bit expensive. 

I've been using the solution for about 15 years. 

The solution is stable. There are no bugs or glitches. It doesn't crash or freeze. 

I'd rate the solution's reliability between seven to nine out of ten. 

We have about 30 to 40 users leveraging it in our organization. In my department, seven to nine people are using it. The users are mostly in IT.

From my side, I have never reached out to support. 

I have used many different solutions previously. I like solutions that offer the minimal amount of coding possible. 

The initial setup was quite complex for organizations. For individuals or students, however, doing a small setup, it's not too difficult. 

I had some help with the initial setup in order to navigate the complexities. I have done some trial versions by myself, however, as there aren't cybersecurity restrictions for a small setup like that. 

My understanding is the solution is expensive. I don't know the exact price.

There is a 30-day trial and discounts for students. 

I'm an end-user.

I'm working with version 26 or 27.

I'd rate the solution seven out of ten. 

With this product, you do need to have a good coding background. 

I'd recommend the product to others. It is quite useful. However, the challenge is always the price. Often, when people hear the cost, they show less interest.

I use it to analyze social and medical data.

I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well.

The automated statistics testing and principle components analysis are very useful as well.

I've also found the decision tree elements pretty useful too.

IBM SPSS Statistics could be cheaper.

There is a learning curve; it's not very steep, but there is one.

I've been using this solution for about 30 or 40 years.

It's been stable for 40 years.

I've never found a dataset that it couldn't handle, but then, my datasets are mainly, perhaps, about a 100,000 cases. Within that range SPSS Statistics does it very easily.

Technical support staff have been very quick and very good.

Before IBM SPSS Statistics became available, I wrote the code myself in ALGOL, FORTRAN, and BASIC, which were the languages at that time. There was no such thing as a statistics package available then.

For me, the initial setup was completely straightforward. I just downloaded it from the university website.

I was done in under two hours.

We have seen enormous ROI.

It's quite expensive, but they do a special deal for universities. So, I use it through the university.

I looked at SAS and Stata. They just seemed much more cumbersome and difficult to use.

I've used PSPP, the freeware version of SPSS, which is clumsy. However, it still does much the same job, at least, for elementary tasks.

If you do it using the graphical user interface, always click on the save button or paste button, not just the save. For example, if I need to analyze some data before I run it, I set it up using the GUI, I click on paste, and then I run it and save it. When I click paste, it follows all the instructions I've given it in the GUI, but it writes the underlying code. I can save the code, on my disc, and I can get it back later.

This means that you can make your analysis completely replicable. You don't have to redo it, you can just rerun the same program.

I would rate this solution at nine on a scale from one to ten.

Our primary use case is to generally survey results and basic cross-tabulation for any ad hoc requests from key stakeholders. At times, it's a high amount of data but when we run on SPSS, it slows down the computer or the laptop, because if the data is huge, then we need a faster computer. But the corporate computers that we get from our company might not take too much of data load.

The solution is quite robust. I wouldn't pick one most valuable feature, but everything is quite handy. If you want to do a quick analysis, SPSS is quite robust and quicker in terms of providing the output. Python does take large sets of data, and it has more functionalities, but in terms of quick turnaround, I think SPSS is quite good.

From an improvement standpoint, I could compare to PyCharm and see how many other things you can automate things. In PyCharm you use Python and have a lot of packages. SPSS is missing out on some of the packages. In upcoming releases, the solution could be more automated. It should have automation of the packages such as being used in R software and Python packages. They use a tremendous amount of packages. If SPSS can follow that suit, I think it would be very beneficial for SPSS.

I've been working with the solution for more than ten years.

Stability is very good if you have a laptop that has good RAM and a good, powerful laptop, then SPSS can take up really huge amount of data. Otherwise, it slows down the laptop. The limitation is processor issues.

Scalability is also limited, but if you have a high-speed computer, then scalability will be better. But compared to PyCharm and Python and R, it's very limited.

The initial deployment is quite straightforward for SPSS.

I use the solution daily. I use quantitative software for both SPSS and NVivo. I use a lot of functions from SPSS: chi-square, regression analysis, linear regression, multiple regression, cross-tabulation.

SPSS is quicker than comparable software. It starts immediately. For basic and intermediate functions, SPSS is quite good. But once it gets advanced, it's better to use open-source software, like Python and R.

I would rate the solution a seven out of ten, and I would recommend the solution to somebody looking to implement SPSS for statistics for their own organization.

We use SPSS specifically for doing segmentation analysis and customer analysis including various kinds of share model predictions, etc.

The solution has numerous valuable features. We particularly like custom tabs. It's very useful. We end up analyzing a lot of software data, so features related to custom tabs are really helpful.

All of the clustering for multi-related techniques including clustering, factoring, etc. is quite useful.

The cost integration features are very good.

The data preparation skills need improvement. When I compare the solution with other tools or competitors, this solution needs to simplify data preparation. 

The solution needs more planning tools and capabilities.

I've been using the solution for about ten years now.

The solution is very stable. I haven't come across or heard of any problems on the solution. There's no bugs or glitches. It works well.

I don't believe this solution would be the best for companies that need to scale. It doesn't have the level of scalability available to grow very much.

I haven't been in touch with technical support directly, but I have been using their forums to help troubleshoot issues. I've researched some forums. Whenever I encounter issues within the solution, I will actively browse a few forums for blogs for documentation that might provide me with some insights.

I have previously used different solutions. I've used SAS, R, and Minit. There are many other solutions as well that I have tried out at one time or another.

The initial setup is very straightforward. We didn't have any issues with the implementation.

I didn't actually deploy the solution, so I can't speak to how long it took. We use different tools as well that I work with. I can be deployed, but I'm not sure how long it would take an organization exactly.

We have an enterprise-level license with IBM.

Although we're working with IBM right now, we're currently looking for a new data science platform solution. I was hoping to find an open-source tool that could fit our needs in the future. We're evaluating R and Python right now, but they're not quite what we need. On all of our new engagements, we'd really like to use open-source only.

We're an official IBM partner. We have an enterprise license; I'm not sure if we're currently using the latest version or not. We might be on V3 or V4.

I'd recommend the solution to other organizations.

I'd rate it nine out of ten.

I primarily use the solution for data analysis.

Some time I have used it RFM analysis, in sales. It has given good insight for improvement

The tests, videos, and tools that are the most useful depend on what objective the company has, but all of the features are quite good.

The solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS.

One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated.

I've been using the solution for one or two years.

The stability of the solution is good. We've never faced any issues.

The solution is scalable.

I haven't really used technical support. Mostly I use Google to look for answers to my questions.

We currently use both SPSS and Minitabs. We prefer Minitabs, but if we don't find a solution on it, we switch to SPSS.

In comparison to Minitabs, the initial setup was more complex. The solution has a lot of options and we weren't sure which were the best to use, and that made the experience frustrating. In the end, the deployment took longer than Minitabs.

NA

not calculated

I'd advise users to think about using Minitabs. The solution is simpler. However, if you are working with big data, SPSS is better. For large data sets, there's nothing better than SPSS.

I'd rate the solution eight out of ten. I'd rate it higher, but it's quite a complex product.

I've used SPSS for my doctoral research and in my work as an academic and consultant. It's useful for getting reliable insights into survey data and performing quantitative data analysis. SPSS does the math for statistical research. 

In theory, I could take the same data set, plug it into an Excel spreadsheet, and eventually get the same result. However, it would be unbelievably messy and the chances of getting accurate and reliable results are next to nil. They're just too complex. For example, if you're trying to do multivariate analysis to find correlations between complex and diverse data sets, you can make a scatter plot in Excel, but it's unlikely to yield satisfactory results.

I use both the formula-based input side of it and the more user-friendly side of it, depending on the context. Both of them produce more accurate, reliable, and easy-to-generate results than any other tool that's around. At the same time, SPSS isn't a tool you should use for simple, descriptive analytics.

If you only need to create a bar chart, it's not worth spending the time to clean your data set and go through all the work required to import it into SCSS. While it can obviously do all those functions, it's not designed to make pretty charts. In other words, it's the hardest way to do the simplest of tasks, but it is the easiest way to do the hardest of tasks.

SPSS is the way to go if you have data amenable to quantitative analysis, and you need high-accuracy results. 

SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous. 

I'll typically take the output data and recreate the chart in Excel. My consultants expect glossy, readable charts, graphs, tables, etc. SPSS has functions to edit and change color, font, spacing, etc., but it's unbelievably fiddly, and I gave up. It just wasn't worth the time. It was way too time-consuming and difficult. 

Generally, it's a challenging piece of software to use. IBM claims it is easy to learn, use, and apply, but it's not. There is a steep learning curve, but it's worth the time. You can't just plug any data into SPSS and say "Go." It has to be properly formatted and cleaned before it will be used. I guess it's a professional tool.

In the future, I would like to see some a template tool or a data-screening tool that would assist with identifying where and how a data set needs to be cleaned. It wouldn't have to tell you exactly what you need to do, but it would be helpful to have something that points you to what needs to be done in order to make the data more compatible with SPSS.

I used SPSS Statistics extensively from 2016 until 2019, and then I started using it again in 2021.

I can't think of a time when SPSS ever crashed on me.

SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools. 

SPSS is incredibly easy to set up.

SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced.

I rate IBM SPSS Statistics nine out of 10. There's a steep learning curve, and you need to take the time to develop the required skills and give yourself enough time to start the process of learning on your own. When IBM advertises how easy it is for you to learn, use and apply, that's true in a sense. However, that's only after you pass the first extremely steep learning curve. Once you understand the basics and get used to it, you can do practically anything with it.

The primary use case of this solution is for statistical approaches, performing ED tests, and multi-armed bandit tests. It gathers the results that help us to decide on what type of campaign works best, and what type of branding would work best.

The features that I find to be the most valuable are the anomaly detection and its statistics. The clustering statistics are important as well as the usual old-school statistical analysis called ANOVA and ANCOVA. They are critical.

There were some new approaches that I hadn't used before. 

The best part is that they have an algorithm handbook, so you can open it up and understand how it works, and if it is useful, this is very important. Many people don't read these types of handbooks, but they should because it was very useful and I use it a lot.

I don't know if this solution is available on the cloud. If it is then we should be using it because it would be even better. The on-premises version is lax in terms of computational capability, so we have to use a more powerful computer.

Some new tools will be available soon with self-explanatory statistical results, and they have multi-language generations that create automatic reports with detailed explanations of the statistical reports. I wish that they were more advanced.

Some areas that need improvement or should be more advanced are in the reporting. The statistics should be more self-explanatory with detailed automated reports.

You should be able to walk through with the statistical schematics because some of the matters are advanced, and if you don't have a full understanding or you don't remember how to get the desired results then there should be a guide or a walkthrough to help and explain how it should be applied.

In the next release, they should have some new statistical approaches that can be applied, some new memory detection, and new clustering techniques.

Also, some new statistical methods to increase the different model's explainability would be helpful.

I have been using this solution for more than three years.

This solution is stable.

This solution is not scalable.

If I had known or implemented the version, then it may be scalable. The problem is that it's used on the original core and it's receiving a long analysis. It should be able to use multi-cores, and CPU, but it doesn't do anything like that. 

I am the only user.

When you contact support, sometimes it takes a while because they don't know how to help you resolve your issue. In turn, they contact other areas of support and it takes time to get back to you.

The support is just ok, and you have to contact someone who works in the US or in Europe.

Previously I was using SAP Statistics. It was old-school, so I switched to Visual Statistics and it was useful. From there, we switched IBM SPSS Statistics. It is a good solution but it would be even better if it had some automated skills.

The initial setup was a little bit complex.

It took half of an evening to complete the setup and implementation, mainly waiting on support to help with issues.

I did the implementation myself. I did not use a vendor or integrator.

It's a pretty old-school statistical tool but it's useful.

I would recommend it, although there are some better tools available.

I would rate this solution a seven out of ten.