What is R ?

R is an open source programming language with a lot of facilities for problem solving through statistical computing. At the time of writing this, there are more than 5K packages available in CRAN repository. Below are few reasons that make R language stand out and why you should really consider learning the language.

What is R used for ?

R is a language and an environment for everything related to data. But what is ‘everything’?.

It includes statistical computing, data mining, data analysis, machine learning, predictive modelling, quantitative analysis, optimisation and operations research etc – all of which are somewhat inter-related terms.

Who uses all this ?
Data scientists, analysts, statisticians, quantitative analysts, forecasters, bio-statisticians, financial analysts, research scientists. These are some of the professions where R is commonly used. But, is R limited to these guys? NO, and not necessary!

Here are some use cases..

If you are involved with anything directly or indirectly related to math, you should consider to learn and use R.

1. May be you want to predict the number of people expected to visit your shop over the next week, or, what is the right combination of meal combo you should put up for sale so it is of liking for the maximum portion of your customers, or, what plan or product should you offer your customers depending on what they already purchased so there is more chance he/she will take your offering?

2. You are a supply chain fellow who wants to know how much of inventory to stock of each part in which of your warehouses, or perhaps when should you exactly make an order for a part (because it can take a month or so for the new batch to reach your storehouse while your customers are continuing to empty your shelves at an irregular pace).

3. You are a bio-statistician, interested to find out if women over 45 years of age and living in high altitude, are more susceptible to heart related diseases?

Getting it? Well, that’s just the surface! There are innumerable variety of problems that can be unearthed and solved in almost every field // business.

R is not just a software or a programming language or a excellent visualization tool, where you can write algorithms to solve problems. It is backed by the works of a community of statisticians, scientists, and engineers in the form of packages that are freely available for you and everyone to use. The bad news is, you still need to write code. But the great news is the rich collection of packages does the heavy lifting for you, that your options have been widened and efforts to arrive at the solution is minimized. In fact, there is more packages getting created every other day. I think it is ok to say, whenever a new technique/ML method/algo is invented, it almost always, first shows its face in R before being implemented in other platforms. This is mainly because R is the medium de facto used by the researchers, professionals and educational institutions alike.

So what are the advantages of using R ?

1. Unlimited Possibilities!

R is a door to a whole world of problem solving and research through its applications in a number of domains. You may be into quantitative finance,  biologist or a supply chain specialist or anything under the cloud, there is a ton of powerful things you can do with R with much less effort. Currently, there are more than 6.5K packages addressing problems in a vast variety of domains.

2. Open Source

The current version is a result of collaborative effort of programmers, researchers and contributors from all over the world. It gets better by the day.

3. Its Free

What does this mean to you? You can install R and will have access to all future releases, updates and the powerful packages at CRAN always available to you free of cost.

4. Excellent documentation

The creators of R has laid down a structured approach into the documentation procedure right at the beginning. So it is a lot more easier to get around compared to other open-source alternatives.

More educational institutions, researchers and authors have adopted R as their primary medium of work. This means the latest techniques, books and research papers publish their findings in R before getting implemented in other software.

5. R takes care of many things behind-the-scene so you can focus more on problem solving

Compared to other popular alternatives, R throws lesser errors, especially with respect to data formatting, etc. This is because R takes of many things in the background. Comparatively, R users spend much less time on debugging and data formatting and rather focus more on problem solving approaches and solutions. It gives more control to the user. You will soon be super-fast and efficient as most tenured R programmers are. You will probably appreciate this more when you get your hands wet.

However, R is said to have a steep learning curve. As with learning any programming language, you will have to crawl before you walk, but the fruits of your efforts will be multiple folds compared to the ‘pain’ of the learning exercise. R is a preferred language for data science and problem solving. A number of corporations are setting up their own in-house data science factory which has created a huge demand for knowledgeable data science workers.

Because of its potential to create enormous value, R programming is arguably the the highest paid skill as of 2014!

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