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Most Popular R Programming Interview Questions with Answers to Help You Get Started

Posted on October 3, 2018October 3, 2018 by Dexlab

Most Popular R Programming Interview Questions with Answers to Help You Get Started

Brainchild of Ross Ihaka and Robert Gentleman, R programming language was first developed in 1993 with an exclusive and extensive catalog of statistical and graphical techniques and processes, including machine learning, time series, linear regression, statistical inference and lot more.

In the following section, we’re about to talk about top interview questions on R programming –perfect for both freshers and experienced consultants, this interesting interview guide covers almost all the major concepts of R and its applications.

Dive Down!

What is R programming?

R programming is an ideal language used for data analysis, and to build incredible statistical software. It’s widely used for a wide range of machine learning applications.

How to write syntax for R commands?

When you start writing commands in R, start using # in the beginning of the line, so that the commands are written as #division.

How to project data analysis outcome through R language?

The best way to convey the results would be by combining the results of data, code and analysis on a document and present the data for further reproducible research. It would help the user recheck the result and take part in the following discussions. The reproducible research aids in performing experiments easily and solving crucial problems.

What are the data structures found in R programming?

Homogenous and Heterogeneous are two data structures found in R programming. For same kinds of objects, we suggest using homogenous data structures as for Array, Vectors and Matrix. And for different types of objects, it’s better to stick to heterogeneous data structures.

How should you import data in R language?

Importing of data in R is done with the help of R commander GUI – it’s used to type commands and is also known as Rcmdr.

Here are 3 ways to import data into R:

As soon as you select data set from the dialog box, enter the date set name as asked.
R command can also be used to enter data – Data-> New Data Set (It’s only applicable for small data sets).
The user can also import data directly from URL, through simple ASCII file, statistical package or from clipboards.

Highlight the advantages of R programming language.

The user doesn’t get entangled in license restrictions and norms for using R programming.
It’s an open source software and completely free of cost.
It has several graphical capabilities.
It is easily run on a majority of hardware and OS (including 32 and 64-bit processors).

Mention the limit for memory in R.

For a 32-bit system, the memory of R is limited to 3GB. And for a 64-bit system, the limit is extended to 8TB.

With this, hope you are ready to crack a tough job interview on R programming – however, for those, who want to dig deeper into the intricacies of this fascinating programming language, we have fabulous R programming courses in Gurgaon. With them discover the path towards a dream career!

The blog has been sourced from — www.janbasktraining.com/blog/r-interview-questions-answers

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Conducting Intensive Workshops – A Holistic, Exhaustive and Multidimensional Approach to Learning

Posted on March 30, 2017March 30, 2017 by Dexlab

“Knowledge was scattered treasure; education organized it into art, commerce and science.”

― Amit Kalantri – a magician, mentalist and an author

St. Stephen’s College, Delhi presents the magnanimous Academic Conclave 2017 – an initiative to endorse intellectual exuberance of the college and to strengthen interdisciplinary education across myriad fields of study. Often, the term ‘Academics’ is misinterpreted as ‘boring’ but once you attend this stellar event, you will definitely get a sneak peek of a perfect amalgamation of enthusiasm and comprehensive knowledge offered to the up-and-coming scholars of India. The intent is to establish a common accessible platform for incubation of ideas, interaction of thoughts and infestation of intellectuality and what can be better than host interactive workshop sessions! Besides lectures and keynote addresses, workshops are being conducted to encourage an easy interaction between the students and stalwarts of specific domains.

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Banking Business and Banking Instruments

Posted on May 26, 2016May 23, 2020 by Dexlab

Having discussed some amount of mandatory regulatory compliances for banks over the past couple of blogs, let us now focus on the bank’s lines of business. Understanding the different banking products is inevitable for credit risk management and analytics. One has to be well versed with the nature of banking products before they step in to develop model for any of them. Each banking product has its own characteristics and its own set of risk exposure. Hence, understanding these products is the top priority. In this blog we discuss three of the major banking products: Checking Accounts, Savings accounts and Certificate of Deposits.

Checking Accounts: This is a transactional deposit account held at a financial institution that allows for withdrawal and deposits. Money held in a checking account is liquid, and can be easily withdrawn using checks, automated cash machines, and electronic debits among other methods. It allows for numerous withdrawals, unlimited deposits etc. These accounts are known as current accounts in UK. These are often loss leaders for large commercial banks since they become highly commotized. Because money held in checking accounts is so liquid, aggregate balances nationwide are used in the calculation of M1 money supply. Continue reading “Banking Business and Banking Instruments”

The Limitation of R Programming

Posted on April 2, 2016April 11, 2016 by Dexlab

R Programming is sort of the darling of the academia and researchers as well due to the cutting edge tools of data science and analytics that it offers. Not only does its open source nature ensure that contributors to the project are able to come out with packages that facilitates in making R Programming be able to sport the latest advances in its field but also make it a option that may be implemented with burning a hole in ones pockets.

The Disadvantages of R

In spite of all its flexibility, R is found want in a number of specific situations. R cannot scale properly with large sets of data. There have been a number of efforts to overcome this significant disadvantage of R, but these efforts have not met with much success and the bottleneck remains an issue which needs to be dealt with seriously.

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The evolution of Big Data in business decision making

Posted on March 19, 2016May 3, 2019 by Dexlab

Big Data is big. We have all established that, and now we know that all the noise about Big Data is not just hype but is reality. The data generated on earth is doubling in every 1.2 years and the mountainous heap of data keep streaming in from different sources with the increase in technology.

Let us look at some data to really understand how big, Big Data is growing:

The population of the world is 7 billion, and out of these 7 billion, 5.1 billion people use a smart phone device
On an average every day almost 11 billion texts are sent across the globe
8 million videos are watched on YouTube alone
The global number of Google searches everyday is 5 billion

But the balance has long been tipped off as we have only been creating data but not consuming it enough for proper use. What we fail to realize is the fact that we are data agents, as we generate more than 25 quintillion bytes of data everyday through our daily online activities. The behaviors that add more numbers to this monstrous hill of data are – online communications, consumer transactions, online behavior, video streaming services and much more.

The numbers of 2012 suggest that world generated more than 2 Zetabytes of data. In simpler terms that is equal to 2 trillion gigabytes. What’s more alarming is the fact that by the year 2020, we will generate 35 trillions of data. To manage this growing amount of data we will need 10 times the servers we use now by 2020 and at least 50 times more data management systems and 75 times the files to manage it all.

The industry still is not prepared to handle such an explosion of data as 80 percent of this data is mainly unstructured data. Traditional statistical tools cannot handle this amount of data, as it is not only too big, but is also too complicated and unorganized to be analyzed with the limited functions offered by traditional statistical analysis tools.

In the realm of data analysts there are only 500 thousand computer scientists, but less than 3000 mathematicians. Thus, the talent pool required to effectively manage Big Data will fall short by at least 100 thousand minds prepared to untangle the complex knots of intertwined data hiding useful information.

But to truly harness the complete potential of Big Data we need more human resource and more tools. For finding value we need to mine all this data.

Then what is the solution to this even bigger problem of tackling Big Data? We need Big Data Analytics. This is more than just a new technological avenue, but on the contrary this is fresh new way of thinking about the company objectives and the strategies created to achieve them. True understanding of Big data will help organizations understand their customers. Big Data analytics is the answer behind where the hidden opportunities lie.

A few advanced tools that are currently in use in the data analysis industry are: SAS, R Programming, Hadoop, Pig, Spark and Hive. SAS is slowly emerging to be an increasingly popular tool to handle data analysis problems, which is why SAS experts are highly in-demand in the job market presently. To learn more about Big Data training institutes follow our latest posts in DexLab Analytics.

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Why “R in Action” Sizzles in Smoke among R Programming Aficionados

Posted on November 1, 2015April 11, 2016 by Dexlab

Data Scientists are much in demand these days and almost everyone wants a part of the pie. You might wonder whether the second edition of “R in Action: Data Analysis and Graphics with R” up to the task. Read on to find out.

The first edition was released way back in 2011 and received a warm reception among those with an interest in R Programming. To state the review of the second edition in a nutshell- it does not disappoint.

Geared towards statisticians coming to terms with R, this book will however leave programmers wanting to get acquainted with R, without much clue.

That does not mean that the book lacks detail about the fundamentals and intricate concepts associated with R. It just means that those who actually have some statistical work to do will derive greater benefits from it. This book is pitched towards the people who are wondering about how to do a certain task that they are able to do in another statistical package.

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Twelve Great Free R Programming E-books

Posted on October 18, 2015October 4, 2017 by Dexlab

To Big Data enthusiasts R is word or rather a letter that needs no introduction. R programming is a programming language that brings the complex world of statistics and datasets at your fingertips. It is mainly used for computing statistics and relevant graphics. The following twelve e-books are not only useful to bring you up to the task for R programming but best of all they are free.

Learning Statistics with R
Author: Daniel Navarro

If you are looking for a guide that will take you through the intricacies of developing software with R be it the basic types and structures of data to more complex topics like recursion, closures as well as anonymous functions. Knowledge of statistics, although helpful, is not an essential pre-requisite .

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