1 / 15

R vs Stata: Which One is Best For Data Science?

Get to know which one is best for Data Science. Here is the indepth comparison between R vs SPSS to find out which one is best for data science.

Télécharger la présentation

R vs Stata: Which One is Best For Data Science?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. R VS STATA WHICH ONE IS BEST FOR DATA SCIENCE? STAT ANALYTICA Presented by: Statanlytica

  2. Presentation Outline Overview R definition Stata Definition R vsStata Ease of Learning Online Support Cost Updates Applications R Applications Stata Applications Conclusion (R vs Stata) Key topics for discussion

  3. Overview Today we are going to discuss the comparison between R vs Stata. It is always overwhelming for the students to compare them for data science. As a statistics students you should know which one is best for data science between R vs stata. Before we get into in depth comparison, we should have a look on the definition of both of these.

  4. R definition R is one of the most influential and most reliable statistics languages in the world. It is used for statistical computation and graphics. It is offering high-level graphics, interface to other languages, and debugging facilities. R is known as the predecessor of the S language. It was designed in the year 1980s and has been used by the majority of statistical communities around the world. But the official release of R was in the year 1995. The primary motive behind the development of R was to allow the academics statisticians to perform complex data statistical analysis. R is derived from that initials of two developer’s name i.e., Ross Ihala and Robert Gentleman. Both of them were associated with the University of Auckland when they developed R. Stat Analytica

  5. Stata Definition Stata is one of the most popular and widely used statistical software in the world. It is used to analyze, manage, and produce a graphical visualization of data. The primary use of Stata is to analyze the data patterns. Researchers are using Stata in the field of economics, biomedicine, and political science. Like only a few software, it offers you the command line as well as the graphical user interface that makes it more powerful. It was created in the year 1985 by StataCorp. Stata is the most compelling statistics software; that’s why it is used in more than 180 countries around the world. And thousands of professionals and researchers trust on this software. Stat Analytica

  6. R vs Stata IN DEPTH COMPARISON

  7. Ease of Learning It is quite complicated for the statistics students to learn R from scratch. The reason is R is a programming cum scripting language. It is pretty hard for anyone to learn a new programming language without having a programming background. But, you can learn R with the help of some free sources provided by R. On the other hand, learning of Stata is quite easy as compared with R. Because learning software is always easier than learning a programming language from scratch. Like R programming Stata also offer the community support to the users. In their community support, you can find other users who can help you while you face problems using Stata. Apart from that, some experts in their community can help you to learn Stata. Stat Analytica

  8. Online Support As we have already discussed that R is an open-source programming language, it means that it is free to use for anyone. Therefore you may not find any official support for the R programming language. But you can find help with R using its documentation, community support, manuals, journals, etc. On the other hand, Stata is a paid software, and every paid software is known for its online support or after-sales support. Stata is offering extensive support to its users, from online support to FAQs, documentation, video tutorials, web resources, Stata news, and webinars. You will never find yourself out of resources while using the Stata software. Stat Analytica

  9. Cost R is free to use for everyone. You need to install it from the internet, and you can run it without paying a single penny to anyone. On the other hand, Stata price starts at $179.00 per year per user. Stata offers different versions for students, education, government, and business. It also provides the new purchase, upgrade, and renew facility of the packages. The license is also divided into two categories i.e., single-user, multi-user, and site license. Stat Analytica

  10. Updates R offers a variety of updates at regular intervals, and you can get the latest update of R on its official site. Apart from that, R also provides updates on its packages that allow you to stay updated with the data science environment.  On the other hand, Stata also get the latest update on a one-year interval. You can get the latest update with the licensed version of Stata. Stat Analytica

  11. R APPLICATIONS R is also one of the most popular tools for exploratory data analysis. It has one of the best data visualization library that is known as ggplot2. The primary use of R is in descriptive statistics. It is used to summarize the main features of the data. Apart from that, R is also used in a variety of other purposes like measurement of variability, skewness, and central tendency. It also allows you to do hypothesis testing that can be used to validate statistical models.It is quite easy to organize the data and data preprocessing in R with the help of its tidyverse package. Eshiny is the most interactive web application package in R. You can use this package to develop interactive web applications that can easily be embedded on web pages.

  12. STATA APPLICATIONS Stat’s GUI offers menus and dialog boxes. With the help of these dialog boxes, users can access plenty of useful features i.e., data management, data analysis, and statistical analysis. You can have easy access to the data, graphics, and statistical menu. Stats offers the easy to use graphical user interface. It is quite simple to use because it uses the point and clicks GUI. The best part of its user interface is can adapt to the different type of users i.e. newbies and the experienced one. No one will ever face any problem while using Stata. You can also create graphs in stat more effectively. Stata allows you to create graphs in both of the ways; the first one is merely pointing and clicking, and the second one with the help of the command line. Stata also offers a set of advanced components that allows you to work more efficiently. You can use a data editor that will help you to see that live data while using the functions and perform operations.

  13. Conclusion Now we have seen the in-depth comparison between R and Stata. R is a programming language that allows you to do a lot more than you can do with the Stata. I would like you to recommend R for data science if you do have a basic knowledge of coding, or you are familiar with the coding environment. On the other hand, if you have some coding knowledge or no coding knowledge, then you should choose Stata over R. Because it is quite easy to use and anyone can use it effectively. The beginners need only prior training to use it like a pro. But if budget is a big issue for you, then you should choose R. you can get the excellent command over R with the help of a few month’s training. Stat Analytica

  14. WEB ADDRESS https://statanalytica.com EMAIL ADDRESS info@statanalytica.com Get In Touch With Us

  15. Follow us on Social Media @statanalytica @statanalytica @statanalytica

More Related