Comparison between R and SAS
R and Statistical Analysis Software (SAS) have been used in data manipulation for years. They both provide users with effective tools and features that allow them to perform mathematical operations and draw meaningful conclusions from data. For that reason, making a choice between the two has been a long-lasting debate in the world of data analysis and data science, which is why we have decided to do a comprehensive comparison between R and SAS. But before that, here is a brief overview of the two software packages.
R
R is generally a programming language used by data analysts and data scientists to manipulate data, build statistical models, and visualize information. It offers inbuilt features for performing calculations, organizing data, and creating graphical representations, which has made it popular among major organizations like Facebook, Airbnb and Google. For more information about R and how it is utilized in data analysis, connect with our R assignment help experts.
SAS
SAS is a statistical software application used for data analysis. It allows companies to carry out qualitative processes that help improve employee productivity and increase business profits. SAS can be used to extract and categorize data, which enables researchers to recognize patterns and trends in data that help in forecasting. With SAS, one can perform effective data management, predictive analysis, as well as business intelligence processes, which can help a company perform efficiently in the ever changing business conditions. To further explore SAS and what it can do in regards to data analysis, reach out to our SAS assignment help experts.
Differences between R and SAS
To have these differences explained in detail by someone who has a knack for R and SAS, link up with our R assignment help experts.
| R | SAS |
| This is an open source software, which means it can be downloaded and used by anyone. | This is a commercial software application, hence, it requires a certain degree of financial obligation. |
| Has a steep learning curve, as you need to know how to code for you to use it. | Easy to learn and can be used by even those who have limited skills in coding or SQL. |
| Since anyone can use R, sharing files with other users is much easier. | You cannot share files that are created with SAS with another users unless he/she is also using SAS. |
| With the popularity of R increasing every day, the software has witnessed significant growth in the past years, resulting in a rapid increase in its market share. | SAS is currently facing huge competition from R, which has resulted in a gradual decline in its market share. |
| Has poor graphical support. | Has impressive graphical support but it does not allow any customization. |
| Offers integrations for advanced deep learning. | Deep learning in SAS has not fully developed and a lot of work need to be put in for this to become an effective feature. |
| Best features include data analysis, flexible statistical analysis, and high interaction. | Best features include variables, nested rules, mix-ins, and functions. |
After a good look into both of these tools, we can confidently say that each tool has its own group of users. Which one you choose for your data analysis will depend on the task at hand and what you wish to achieve. If you want to carry out impeccable analyses on budget, however, our SAS assignment help experts recommend that you go for something that is open source. In this case, R will be the best option.