R and SPSS are both the closest competitors to each other. Both of them are widely used for statistical data analysis. 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 Programming

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

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.

**R vs SPSS**

**Updates**

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 are contributing to updating the R programming. That is why it is getting faster updates. There are hundreds of libraries that 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 specs r, R programming is the clear winner.

**Platform**

The core code of R programming is written in C and Forton. It is a completely 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. It offers the best in the class graphical user interface that is used for interactive and statistical analysis.

**Decision Tree**

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.

Whereas IBM SPSS has full support for decision trees. It is quite handy to work with the decision tree in IBM SPSS because of its simple and clean interface.

**Interactive**

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.

**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 any graphs to showcase your data.

In comparison, SPSS has limited support for data visualization. You can only create the basic as well as simple charts and graphs in SPSS. In this comparison of r spss, R programming is the clear winner.

**User Interface**

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. 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 software.

**Data Management**

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. It offers the sorting, aggregation, transposition, and merging of the table.

**Documentation**

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.

**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 then you can have multiple options to get good command over it.

On the other hand, SPSS is quite easy to learn for beginners. It has a GUI that allows users to explore its features with ease. It is easy to learn by anyone.

**Cost**

R programming is an open-source programming language and free to use. It means that anyone can use it without paying a single penny to anyone. On the other hand, you can use SPSS using subscriptions, and one-time purchases. In one time purchase, you can have four editions with a variety of features.

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## Used By Companies

### Major companies using R

- Accenture
- Amazon
- Cognizant
- Deloitte Consulting

**Major Companies Using SPSS**

- MWW Group LLC
- ICF
- Edward Jones
- Nike

Zendesk Inc

## Career Scope

### Career Scope Using R

- R programmer
- Data Scientist
- Data Analyst
- Data Architect
- Data Visualization Analyst

### Career scope using SPSS

- Data Quality Analyst
- Business Analyst
- Data Analyst
- Data Processing Specialist
- Data Engineer

## Uses

### Uses of R

- Data Analysis
- Data Science
- Machine Learning
- Statistics
- Research

### Uses of SPSS

- Data Collection
- Data Analytics
- Statistics
- Manufacturing Process
- Market Research

## Features

### Key Features of R

- Open-source
- Strong Graphical Capabilities
- Highly Active Community
- A Wide Selection of Packages
- Comprehensive Environment
- Distributed Computing
- Cross-platform Support

### Key Features of SPS

- Faster processing
- Data integration from various sources
- Deep statistical capabilities
- Data Management
- Statistics models
- Intuitive user interface
- Advanced data visualizations

## R vs SPSS (Tubular Form)

Basi

Basis for Comparison | R | SPSS |

User Interface | R is an ancient programming language that is offering an interactive interface to the users. Although R is a programming language that is based on programming concepts. But you can have a Graphical User Interface with Rstudio | SPSS is a software that is created by IBM. It offers an interactive user interface that is user-friendly as compared with R Programming. Apart from that, it is quite similar to excel which is easy to use. |

Decision Making | R is one of the greatest programming languages for efficient decision-making. It offers a variety of packages such as Classification and Regression Tree (CART). But you need to have some programming skills to get most of it. | IBM SPSS offers easy to use beginner-friendly interface for quick decision-making functions for the users. |

Data Management | Data management is one of the areas where R programming lacks a lot. When we try to use any functions within data then it first loads all the data into the memory and then loads the function too. Therefore it is not suitable for fewer amounts of data. | SPSS offers better memory management when it comes to the limited amount of data. It has a lot of data management functions i.e. sorting, aggregation, and transpositions. Data merging and many more. |

Documentation | R has one of the largest documentation in the world. There are lots of documentation files available in the world. It also has one of the strongest communities 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 its limited use, it doesn’t have one of the best documentation in the world. |

Platform | R is built with C programming and Forton programming language. It is designed and developed for statistical computing and offers all object-oriented functionalities. | SPSS is built with Java programming. It is a statistics software that offers quite easy to use interface for statistical analysis and is packed with lots of tools. |

Cost | R is an open-source programming language and it is free to use for anyone. Even anyone can contribute to its development with the help of libraries and packages for R. | SPSS is a paid software offered by IBM. If you want to get use SPSS for your business then you need to have its license. Apart from that if you want to experience it once then you can have a free trial of it. |

Visualizations | R is one of the finest programming languages for data visualization. It has plenty of models such as ggpot2 that are used to create customized graphs for data visualization. | If you love to use GUI in SPSS then you will find it hard for you to create customized graphs in SPSS. For this, you need to use a command-line interface. But still, it will not match the level of R programming. |

## R vs SPSS Popular Questions

### 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

Within this most competitive world. 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 studio vs spss

Rstudio is an open-source tool used for R programming. If you are not good with command line programming then Rstudio is quite helpful for you to analyze data and create a visualization with ease in R programming.

On the other hand, SPSS is a statistical analysis tool that offers plenty of features for data management, data analysis, data visualization etc. It is quite easy to process data using SPSS without having any coding language.

RStudio is an open-source tool that uses the R programming language to analyze data and create visualizations. IBM SPSS is used for statistical analysis and has features that make it easier for individuals without coding knowledge to analyze large datasets.

## Is R better than SPSS?

Overall R is far better than SPSS, but for this, you need to have some programming skills because it works with object-oriented programming paradigms. On the other hand, SPSS offers you a strong graphical user interface that is written in Java and quite easy to use, if you have no programming background, you should have great statistical analysis skills to get most of SPSS.

## Why is R so good for statistics?

R is built by statisticians for statistics. What does it mean? It means that R is an object-oriented programming language that is specially built to perform statistics operations and create statistical models. Apart from that, it offers a large number of R packages that allows you to perform statistical analysis with ease.

## Can you use R with SPSS?

One of the greatest or prime features of SPSS is that it allows you to do integration with other tools and programming languages. Therefore you can easily use R with SPSS. You can use R functions in SPSS while maintaining the integrity of the original database.

**Conclusion**

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. R requires some training to master the concepts. And you should also have the 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, data analytics can be easily done in SPSS. 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 once you are done with those concepts, you will do lots of R programming tasks with ease. But if you want to do data analysis within limited functionality, then you should use SPSS.