SMU Data Science Review
Abstract
A quantitative analysis will be performed on experiments utilizing three different tools used for Data Science. The analysis will include replication of analysis along with comparisons of code length, output, and results. Qualitative data will supplement the quantitative findings. The conclusion will provide data support guidance on the correct tool to use for common situations in the field of Data Science.
Recommended Citation
Brittain, Jim; Cendon, Mariana; Nizzi, Jennifer; and Pleis, John
(2018)
"Data Scientist’s Analysis Toolbox: Comparison of Python, R, and SAS Performance,"
SMU Data Science Review: Vol. 1:
No.
2, Article 7.
Available at:
https://scholar.smu.edu/datasciencereview/vol1/iss2/7
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Included in
Applied Statistics Commons, Other Computer Sciences Commons, Programming Languages and Compilers Commons, Software Engineering Commons, Statistical Methodology Commons
