Today we are going to discuss the comparison between R vs Stata.
It is always overwhelming for the students to compare them to data science.
As a statistics student, you should know which one is best for data science between R vs stata.
Before we get into a depth comparison, we should have a look at the definition of both of these.
R programming 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 the initials of two developer’s names i.e., Ross Ihala and Robert Gentleman. Both of them were associated with the University of Auckland when they developed R.
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.
R vs Stata
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.
R is an open-source programming language and has a community for developers where anyone can showcase their expertise.
Apart from that they can also help each other if anyone is facing the problem with R code.
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 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.
Stata also offers extensive learning support to users in the form of blogs, tutorials, webinars, training, journal, etc.
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.
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.
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.
- 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.
- 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.
- R is offering the best way to analyze both discrete and continuous probability distribution.
- 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.
- You can also develop predictive models in R that works with the integration of machine learning algorithms that help you to find the occurrence of future events.
- 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.
- 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.
- Stata is a developer and programmer-friendly because it offers the command line feature. Its command line has a set of features that allows programmers to type the command and run them. The programmers can type the command scripts and syntax and then run the commands. The solutions of the command will respond and show the results in the result windows.
- 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.
- It also offers the data management capabilities that allow you to have full control over data sets. You can link the data set together and reshape them quickly with the help of Stata. Apart from that, you can also define, edit, and manage variables in 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. In the command line, you need to write the script that continuously comes up with a large number of graphs. You can use these graphs in printing, publications, and export. It supports multiple file formats such as EPS, TIF, PNG, and SVG. You can also edit the graph in Stata using the integrated graph editor in Stata.
Conclusion (R vs Stata)
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 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.
The training will cost you some money, but it will help you to use the free language for a lifetime.
Now it’s over to you which one you prefer between R vs Stata.
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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.
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.