R and SPSS are both the closest competitors to each other. Both of them are widely used for statistical data analysis. However, there are a lot of differences between R vs SPSS. The major difference between SPSS vs R is that R is a programming language, whereas SPSS is a software created by IBM. Let’s start the comparison between them with a quick introduction to both of these statistical tools or languages.
R is a multipurpose open source programming language. It is considered one of the best programming languages for data analytics. R is a command-line-based programming language. There is limited support for the graphical user interface. But you can get the GUI in R programming with the help of R studio. You can extend the features of R with the help of the packages. R is the best programming language for data visualization.
SPSS stands for statistical package for social science. It is the product of IBM. SPSS is a GUI-based software. Therefore it is quite easy to perform a variety of operations in SPSS with just simple clicks. SPSS doesn’t support the packages, but it gets regular updates from IBM. SPSS has limited support for data visualization.
Is SPSS still use
Yes, there are a large number of people in the world who use SPSS. It is one of the finest statistics software in the world. Apart from that, it is offered by IBM with great support. But due to technology enhancement, the users of SPSS are now declining. SPSS is not as powerful as R programming for data science and data analysis.
Why R is the best statistical software
R is one of the leading statistical software in the world. It is offering almost every feature that data analytics and data science use in their daily routine. It is used for statistical computation and graphics processing. You can find lots of packages and libraries with R programming.
Is r studio similar to SPSS?
No, Rstudio is not similar to SPSS. Rstudio is an open-source tool for R programming. It makes it quite easy and convenient to analyze data and create a visualization in R programming. On the other hand, SPSS is full of statistical software. It has lots of features for statistical analysis. These features are quite easy to understand, even if you have no coding knowledge to analyze a large dataset.
Is SPSS worth learning
The world is becoming more competitive for tools. Unfortunately, SPSS is not as competitive as other Statistics tools such as R programming and many more. Therefore it is not worth learning SPSS in this competitive world.
R vs SPSS in Tabular Form
|Basis for Comparison||R||SPSS|
|User Interface||R is one of the oldest programming languages that is why It is not offering interactive interfaces to the user. With R studio you can have GUI for R programming. Although it makes it quite easy to learn and practice R and master various steps and commands.||SPSS is a complete software for statistics. That is why it is more interactive and user friendly as compared with R programming. If you are familiar with MS Excel then you are going to love SPSS.|
|Decision Making||For decision making R offers some of the packages that are used for Classification and Regression Tree(CART). But the problem is that its interface is not user friendly for beginners.||For decision making, IBM SPSS is quite better than R programming. If you want to perform decision making then SPSS is the best option for you because of its user -friendly interface and functions.|
|Data Management||R has one of the worst memory management among all the programming languages. Whenever you try to use any of its functions then the function loads all the data into memory before execution. That is why it can handle large amounts of data with limited memory.||SPSS offers better memory management functionality as compared with R programming. It has lots of data management functions such as sorting, aggregation, transposition and for merging of the table.|
|Documentation||R has one of the largest documentation in the world. There are lots of documentation files available in the world. It also have one of the strongest community in the world where you can find documentation from other users.||Although SPSS is a paid software and it has its own documentation. But due to the limited use of it doesn’t have one of the best documentation in the world.|
|Platform||R is built on C programming and Forton. R is one of the leading statistics computing languages with the best object oriented facilities.||SPSS is written in Java programming. That is why it has a better graphical interface. It is also a decent tool for interactive and statistical analysis.|
|Cost||R is free to use programming language because it is an open source software. It is also getting regular and fast updates with its libraries and packages.||IBM SPSS is a paid software. And you need to pay some amount to use SPSS. Although you can have a free trial of SPSS to experience it.|
|Visualizations||R is one of the leading programming languages for data visualization. It is quite easy to customize and optimize the graph in R programming. It has a wide range of modules for graphs such as ggplot2.It is quite interactive that allows the users to play with data.||SPSS is not as good as R for graphical capabilities. It is quite easy to make minor graphic changes in SPSS. But when you need to customize a graph to its fullest then you can find it quite difficult.|
R vs SPSS
R is getting the updates in a shorter period as compared with SPSS. It is an open-source programming language; thus, millions of R programmers contribute to updating the R programming. That is why it is getting faster updates. Hundreds of libraries keep adding in R to make it more powerful and useful for everyone.
On the other hand, IBM SPSS also gets regular updates. But remember that you need to pay for the updates. You can’t get SPSS for free. But yes, you can try the trial version of SPSS. In this comparison of SPSS R, R programming is the clear winner.
The core code of R programming is written in C and Forton. Thus, it is the complete object-oriented programming language. But it just lacks a graphical user interface.
On the other hand, the core code of SPSS is written in Java. Thus, it offers the best in the class graphical user interface used for interactive and statistical analysis.
R doesn’t support the decision tree for statistics analysis. R only supports the classification, and the regression tree as most packages and libraries are not designed for the decision tree. The trees created by R programming do not provide a user-friendly interface.
On the other hand, IBM SPSS has full support for decision trees. Moreover, it is quite handy to work with the decision tree in IBM SPSS because of its simple and clean interface.
When it comes to interactivity, then R is not as good as SPSS. R is offering the command line interface, which is not that easy for the users to do interactive analytical operations.
On the other hand, SPSS is quite convenient to use interactive analytical tools. It has a built-in editor that makes it easy to use for users. But when it comes to using the full potential of interactive analytics, R is best because there are numerous commands for interactive analytics.
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Charts and Graphs
It is quite easy to modify and optimize R’s graphs because of its wide range of packages and modules. R is also one of the best programming languages for data visualization. Data scientists use the ggplot2 and R shiny packages in R for data visualization. It is quite easy to do data visualization in R because you can use graphs to showcase your data.
In comparison, SPSS has limited support for data visualization. You can only create basic as well as simple charts and graphs in SPSS. In this comparison of R SPSS, R programming is the clear winner.
R is an open-source programming language; therefore, it provides a command-line interface like most open-source programming languages. But you can have the graphical user interface in R programming using R studio. But R studio is not free. You need to pay for it. Therefore, I want to suggest you code in R using the command-line interface. You may struggle initially, but you will find it quite easy to use after getting a good command over it.
On the other hand, SPSS offers the best in the class graphical user interface. It offers a user-friendly UI that is easy to use. It is similar to spreadsheet softwares.
R is not that easy to manage the data in R programming. However, R processes a huge amount of data. But the problem is when you need to perform any function on the data. Then the data needs to be loaded into the memory before the execution. In this way, there is a limited number of data that can be handled simultaneously.
On the other hand, IBM SPSS has great data management functionality. For example, it offers the sorting, aggregation, transposition, and merging of the table.
R has one of the best documentation files available over the internet for free. R has the largest community in the world. Millions of R programmers offer the best documentation to beginners. SPSS documentation is not that great because it has limited use, and it is only accessible to the users who have its licensed version.
R is an open-source programming language. Therefore, you need not pay a single penny to anyone for an R programming challenge. It is also getting updates at regular intervals and also keeps updating the new libraries.
On the other hand, IBM SPSS is a paid software. So you need to pay some amount to use SPSS. But if you want to learn SPSS, then you can have the trial version of SPSS.
Easy of learning
R is one of the oldest programming languages, and it has lots of complex syntaxes. That is why it is not beginner-friendly. If you start learning R, then you can have some issues. But once you get started with these programming languages, you can have multiple options to get good command.
On the other hand, SPSS is quite easy to learn for beginners. This is because it has a GUI that allows users to explore its features with ease. Therefore, it is easy to learn by anyone.
Let’s end this battle between R vs SPSS. R is a great programming language for statistics. It is quite easy to implement lots of statistics functions using R programming. However, r requires some training to master the concepts. And you should also have basic programming knowledge before getting started with R programming. Therefore R is not a good option for absolute beginners in data analytics.
On the other hand, SPSS is best for data analytics. You can also perform a variety of statistical analysis operations with SPSS with ease. But when it comes to data visualization, then SPSS has limited options. On the other hand, R has a variety of operations for data visualization. It also has the best support for exploratory data analysis (EDA). In the end, I would like to suggest that you should go with R programming even if you want to work beyond your limits. It will take time to master the concepts, but you will do lots of R programming tasks with ease once you are done with those concepts. But if you want to do data analysis within limited functionality, then you should use SPSS.