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R Programming Tests

    • 17 tests |
    • 234 questions

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Sample R Programming Assessments question Test your knowledge!

When using the R function glm(), what does specifying the family = binomial(link = 'logit') argument achieve?

  • It fits a Gaussian linear model.
  • It instructs glm() to use a binomial distribution with a log link function.
  • It fits a linear regression model with non-constant variance.
  • It fits a logistic regression model.
  • It fits a Poisson regression model.

What is the primary function of the apply() family functions in R?

  • To facilitate machine learning algorithms.
  • To iterate over arrays and lists in a memory-efficient way.
  • To apply a function over the margins of an array or matrix.
  • To create graphical user interfaces within R.
  • To perform asynchronous operations.

What does the term 'lazy evaluation' refer to in R programming?

  • The process of evaluating variables only at the moment they are used in the code.
  • The efficiency gained from compiling R code before execution.
  • The delay in garbage collection until maximum memory capacity is reached.
  • The method of saving intermediate results for reuse in later computations.
  • A debugging feature that postpones error messages until the end of the script.

Given a vector x with 10 million numeric values, which of the following R scripts will efficiently calculate the mean without causing memory issues?

  • mean(unlist(lapply(x, identity)))
  • sum(x)/length(x)
  • Reduced <- Reduce(`+`, x); Reduced/length(x)
  • for(i in 1:length(x)) { total <- total + x[i] }; total / length(x)
  • accumulate(x, `+`)/length(x)

R has several packages for data manipulation. Which package provides the dplyr function select() to subset data by columns?

  • data.table
  • ggplot2
  • plyr
  • dplyr
  • tidyr

What R function allows you to take a script of 'base R' graphics commands and produce LaTeX output?

  • Sweave()
  • latex()
  • tikzDevice
  • ggplot2()
  • knitr()

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R Programming Assessments Tips

1Understand the Basics

Start with fundamentals of R—understand how vectors, lists, and data frames work.

2Practice Data Manipulation

Get comfortable with manipulating datasets, it’s the heart of R programming.

3Brush Up on Statistical Methods

Ensure your statistical knowledge is strong to interpret data correctly.

4Time Management

Practice keeping a steady pace - not too fast, not too slow – and avoid lingering on one question.

5Free Practice on Practice Aptitude Tests

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R Programming Assessments FAQs

What is covered in these tests?

Our R Programming tests cover a wide spectrum of topics, including data manipulation, statistical analysis, data visualization, programming constructs, and more, to fully assess your R skill set.

How do I prepare for R Programming tests?

Preparing for R Programming tests requires brushing up on statistical concepts, practicing coding in R, and familiarizing yourself with common data manipulation tasks and visualization techniques.

Will these tests help me find a job?

These tests can be a valuable technology benchmark for your skill set, aiding in your preparation for job applications that require proficiency in R Programming.

How do employers use these tests?

Employers use these tests to identify candidates with the practical skills needed to handle tasks in data analytics, research, and software development roles that require R expertise.

Where can I practice free R Programming test questions?

Practice Aptitude Tests offers a platform where you can take a variety of R Programming practice tests, which is a great way to prepare for actual assessments.