SPSS Statistics

Data is the most powerful resource of the contemporary era, so powerful in fact, that the limits to its power and what it can be used for are yet to be discovered. It’s already changed the face of every industry on the planet, to varying degrees, caused controversy, saved lives and massively accelerated growth. It also helps you pick what movie to watch on a Saturday night. However, in its raw form, data of any sort is a bit futile. It requires the processing and packaging of a powerful computer to start building it into a tool, for marketing, for predicting the financial market, for making diagnoses and all of the rest of its varied and amazing applications. In trying to unlock all of the applications for data, all sorts of different programs have arisen. One such program is SPSS (Statistical Package for the Social Sciences), released by IBM. Its influence has been extremely steep, and it is the go to for many data and analytics professionals all around the world. But what does it do? And why does it impress so much in its abilities? Well, let’s find out.

What Is SPSS?

Understanding the nature of the program and its origin is vital for unlocking its usefulness at a top level. SPSS is more accurately called IBM SPSS, as it is a product of the International Business Machines corporation’s analytics department. “In short, SPSS is a tool that provides an all-in-one method, or interface for data analysis, in a convenient, user-friendly setting”, explains Rod Lewis, analytics expert at Writinity and LastMinuteWriting. Essentially, SPSS is the tool that can turn the relatively unhelpful raw data material into an extremely helpful resource that can be used for whatever it is the operator or researcher wants.

Ease Of Use Factor

SPSS is appealing for its usability factor, and the realities that it deftly simplifies. Data is tricky; it’s hard to gather, to store, to organize, to understand and to use. And yet, in SPSS, you have a tool that handles the majority of those things, all from within the workspace. “SPSS is an entirely self-sufficient tool, which means that it exists independent of any other scripting and can be used by anyone, even if they don’t have prior knowledge of something like SQL, explains Jaimie Kimber, tech writer at DraftBeyond and ResearchPapersUK. For as complex as data is, SPSS simplifies it.

Protection Against Error

Even though most data operations get handled by machines, there’s still so much that can go wrong, through human error. SPSS is a wonderful tool for avoiding these kind of mistakes. As mentioned above, there is an overall sense of simplicity with the software that already makes life easier. Add to that the fact that it helps protect against mishandling data, gives actionable insights on statistical method and gives you a huge boost when it comes to understanding the results of analysis and you have an immensely powerful tool, that is extremely eager to ensure that the data that you have on your hands stays valuable and doesn’t get misunderstood or mistreated by its owner.

A Lack Of Competition

There are many alternatives to SPSS when it comes to understanding and using data, the most famous of which are probably R and Python. But the truth is that these can’t and don’t compete with SPSS. R and Python are highly technical tools, that can be used by statisticians and data experts as they experiment with data and data reading methodology. But SPSS has the ability to help users who are experts in their field, like finance or entertainment, but who have neither the time nor the inclination to tinker endlessly with data from an abstracted technical viewpoint. This means that SPSS can stand head and shoulders above its ‘competition’ and continue to press forward as the central, consumer option.

Conclusion

With data being so important in the modern era, it’s of vital importance that it can be used effectively when it is collected. If you aren’t careful, it can be like sitting on an oil field without ever bothering to dig beneath the surface. SPSS is the solution to that problem.