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

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STAT ANALYTICA
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Presentation Outline
Overview R definition Stata Definition R vs
Stata Ease of Learning Online Support Cost Updates
Applications R Applications Stata
Applications Conclusion (R vs Stata)
Key topics for discussion
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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.
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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
developers name i.e., Ross Ihala and Robert
Gentleman. Both of them were associated with the
University of Auckland when they developed R.
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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 thats why it is used in
more than 180 countries around the world. And
thousands of professionals and researchers trust
on this software.
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R vs Stata
IN DEPTH COMPARISON
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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.
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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.
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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.
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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.
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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.
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STATA APPLICATIONS
Stats 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.
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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
months training.
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