Skip to main content
HomeAbout RLearn R

What is the Best Statistical Programming Language? Infograph

The infograph 'Statistical Language Wars' compares statistical programming language like SAS, R and SPSS to see how they stack up.
Jun 2014  · 2 min read

A feature that all programming communities have in common is the numerous debates about why their programming language of choice is better, more advanced, faster, holier etc. In today's data science community, it seems as if these discussions are omnipresent with advocates of SAS, SPSS, R, Python, Julia, etc. battling and challenging each other on every online medium on the best statistical programming language. (side note: These 'data driven' debates are often a good example of how you can prove anything with statistics.)

While these debates are a good thing for the community and the programming language as a whole, they unfortunately also have a negative effect on those individuals that are just in the beginning of their data analytics career. Biased opinions on all sides of the table make it difficult for new data analysts to see the forest for the trees when choosing a statistical programming language.

An Infograph for each Statistical Programming Language

Especially for this new group of data analysts (and future debaters), as well as for everyone else that is interested in learning data science or an additional statistical language, we created the infograph 'Statistical Language Wars' that gives a basic comparison between statistical programming languages like SAS, R and SPSS to see how they stack up. This is to provide a more clear starting point.

(To dive in to learning R, try this free introductory course. Also, check out DataCamp's R Data Import Tutorial.)

statistical programming language infograph
Source: datacamp.com/community/blog

We'll make sure to regularly update this infograph based on the feedback you provide, and we will definitely consider to create some new infographs that focus more on other players such as Python and Julia.

Feel free to share!

Learn more about R

Certification available

Introduction to R

BeginnerSkill Level
4 hr
2.6M
Master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets.
See DetailsRight Arrow
Start Course
See MoreRight Arrow
Related

Google Cloud for Data Scientists: Harnessing Cloud Resources for Data Analysis

How can using Google Cloud make data analysis easier? We explore examples of companies that have already experienced all the benefits.
Oleh Maksymovych's photo

Oleh Maksymovych

9 min

40 R Programming Interview Questions & Answers For All Levels

Learn the 40 fundamental R programming interview questions and answers to them for all levels of seniority: entry-level, intermediate, and advanced questions.
Elena Kosourova's photo

Elena Kosourova

20 min

A Guide to Docker Certification: Exploring The Docker Certified Associate (DCA) Exam

Unlock your potential in Docker and data science with our comprehensive guide. Explore Docker certifications, learning paths, and practical tips.
Matt Crabtree's photo

Matt Crabtree

8 min

Bash & zsh Shell Terminal Basics Cheat Sheet

Improve your Bash & zsh Shell skills with the handy shortcuts featured in this convenient cheat sheet!
Richie Cotton's photo

Richie Cotton

6 min

Functional Programming vs Object-Oriented Programming in Data Analysis

Explore two of the most commonly used programming paradigms in data science: object-oriented programming and functional programming.
Amberle McKee's photo

Amberle McKee

15 min

A Comprehensive Introduction to Anomaly Detection

A tutorial on mastering the fundamentals of anomaly detection - the concepts, terminology, and code.
Bex Tuychiev's photo

Bex Tuychiev

14 min

See MoreSee More