R Interview Questions and Answers
R is a robust programming language and software environment used for statistical analysis, graphical representation, and reporting. It is a well-structured, efficient, and straightforward programming language that includes loops, conditionals, user-defined recursive functions, input, and output facilities.
Read our list of r interview questions to get yourself updated on this language which provides an efficient data handling, storage facility, and a suite of operators for various calculations on arrays, vectors, and matrices.
Besides calculation and statistics, R provides a coherent, extensive, and integrated collection of various data analysis tools. Read the r interview questions to understand how R provides graphical facilities for data analysis and presentation on paper or digitally.
R is the world's most widely used statistics programming language. It's the first choice of data scientists and supported by a range of talented community contributors. It is taught in many universities and is also deployed in mission-critical business applications. This tutorial will give you the most commonly asked r interview questions along with relevant examples in simple and clear steps.
Most Frequently Asked R Interview Questions
Here are the correct steps for generating a random walk using the R language:
- Use the arima.sim() to generate a Randomwalk model.
- Now, go to the model argument and set it equal to a list(order = c(0, 1, 0)) for generating a RW-type model.
- After that, set “n” equals 10 sp as to produce 10 different observations and then save this to the random_walk.
- Now, use the ts.plot()function for plotting your random_walk data.
- Next, use the diff() function for calculating the first difference between sets of your random_walk data.
- Now, you can save this as random_walk_diff.
- Finally, you should use another call to ts.plot() to be used for plotting random_walk_diff
There are two ways for transposing rows and columns in R.
- Using t to just transpose the data frame as if it would be a matrix
- Use tidyr::spread along with tidyr::gather
Note: R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests,) and also graphical techniques, which is highly extensible. Read our list of r programming interview questions to get better in this language and even start working on your own data science project!
Note: R provides a wide variety of statistical (linear and nonlinear modeling, classical statistical tests,) and also graphical techniques, which is highly extensible. Read our list of r programming interview questions to get better in this language and even start working on your own data science project!