R and SPSS are strong data science platforms. Both are used to execute statistical analysis of data sets. Large organizations and higher institutions use both R and SPSS. But, R is more often used by people because of its open-source nature and many free possibilities. Similarly, there are various points of difference among them. Students get confused about R vs SPSS. Especially those students who are beginners in programming. That is why they search for R vs SPSS. Are you also one of them? Then, don’t worry! This blog will help you in understanding R vs SPSS. 

 

Read this blog till the end. We will discuss all essential information regarding R vs SPSS. So, let’s start with the overview of R vs SPSS.

 

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R vs SPSS: Overview

 

For statistical data analysis, R and SPSS are the two business tools. R programming language is a free and open-source language. It is widely used in the field of analytics. SPSS, on the contrary, is IBM’s Statistical Package for the Social Sciences. SPSS has built-in facilities for data quality processing and analysis. R is a scripting language with minimal graphical user interface features.

 

R contains several packages that are supported by the community. SPSS, on the other hand, is fully handled by IBM in terms of support and product expansion. R is famous for its customized visualization tools. But SPSS’s visualization capabilities are restricted.

 

R vs SPSS: Key Differences

 

User Interface

 

R: Although R’s analytical tool is less interactive. But, editors are available to provide GUI assistance for programming in R. Analytics R is the finest tool for studying and practicing hands-on analytics. Since it truly helps the analyst in mastering the many analytical procedures and commands.

 

SPSS: The interface of SPSS is more dynamic and user-friendly. SPSS presents information in a spreadsheet-like format.

 

Decision Making

 

R: R does not have many methods for decision trees. Most R packages can only execute CART (Classification and Regression Tree), with a less user-friendly interface.

 

SPSS: Because R does not have many tree algorithms. SPSS is better for decision trees than R. The SPSS interface for decision trees is quite user-friendly and clear.

 

Easy To Learn

 

R: R is a simple to learn open-source programming language. And it is possible to improve one’s mastery of the language.

 

SPSS: SPSS is also simple to learn. Because it has a user interface similar to Microsoft Excel spreadsheets. The only disadvantage is that it is not freely available to users.

 

Features

 

R: The features of R are;

 

1. R is open-source software. 
2. It has a wide community of users that can help you solve difficulties. 
3. Because of its open-source nature, R has a huge number of downloadable packages and programs produced by users. It may be used to analyze datasets. 
4. R also works effectively with several software and database applications.

 

SPSS: The features of SPSS are as follows;

 

1. SPSS has out-of-the-box capabilities and less setup and package downloads. 
2. It has a more accessible graphical user interface and the ability to run scripts without substantial coding skills. 
3. Another benefit of SPSS is that it comes with built-in data cleansing and staging features.

 

Data Management

 

R: One of R’s biggest flaws is that most of its functions must load all of the data into memory before running.

 

SPSS: In terms of data management, SPSS is comparable to R. It offers data management operations. Such as sorting, aggregating, transposition, and table merger.

 

Documentation

 

R: In terms of documentation, R has explanation documentation files. They are readily available. The R community is one of the most powerful open source communities.

 

SPSS: SPSS, on the other hand, falls behind in this area. Due to its limited use, SPSS lacks this function.

 

Platform

 

R: R is written in the C and Fortran programming languages. oR’s object-oriented programming capabilities are superior to most statistical computing languages.

 

SPSS: SPSS uses Java to create the graphical user interface (GUI). It is mostly used for interactive and statistical analysis.

 

Cost

 

R: R is free open-source software. The R community is very quick to update the software and add new libraries.

 

SPSS: If someone wishes to study SPSS, they must first try out the trial version.

 

Visualization

 

R: Because of the large number of modules available in R. There are many more options for customizing and optimizing graphs. ggplot2 is the most extensively used R package. These graphs can also be made interactive. It allows viewers to interact with the data.

 

SPSS: Although it is possible to make simple adjustments to the graph. Fully customizing your graph and visualizations in SPSS may be time-consuming.

 

R vs SPSS: Which companies use them?

 

The companies who use R are as follows;

 

• Facebook
• Twitter
• Google
• Microsoft
• Uber
• Airbnb
• IBM
• ANZ
• HP
• Ford

 

The name of companies who use SPSS;

 

• eBay
• KPMG
• IBM
• Accenture
• Capillary Technologies
• Infosys
• Wipro
• Capgemini
• Cognizant Technology Solution

 

To Sum Up

 

We have discussed the R vs SPSS in the above blog. This blog has explained what R vs SPSS is. We have discussed the main difference between them. Both R and SPSS are analytics programs with a lot of career potential. When it comes to massive data, both R and SPSS are slow. Thus you will need to use another program to handle this problem. Finally, I would like to point out that both R and SPSS are fantastic analytics tools. They can provide wonderful job opportunities. As a result, it is simple to understand and apply. I hope you understand this blog well.