MCQs R Programming Language 2

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This quiz “MCQs R Programming Language” will help you to check your ability to execute some basic operations on objects in the R language, and it will also help you to understand some basic concepts. This MCQs R Programming Language Quiz will also improve computational understanding. Let us start with the test “MCQs R Programming Language” with Answers.

Online MCQs about R Programming Language.

1. What is the benefit of using the R programming language for data analysis?

 
 
 
 

2. A data analyst inputs the following calculation in their R programming:
$$basket_1 * 20 + basket_2 * 15 $$
Which arithmetic operators are the analyst using?

 
 
 
 

3. Which of the following examples can you use in R for date/time data?

 
 
 
 

4. Which of the following statements about RStudio’s integrated development environment are correct?

 
 
 
 

5. A data analyst writes the code summary(penguins) to display a summary of the penguins dataset. Where in RStudio can the analyst execute the code?

 
 
 
 

6. If I have two vectors x <- c(1,3, 5) and y <- c(3, 2, 10), what is produced by the expression rbind(x, y)?

 
 
 
 

7. Suppose I have a vector x <- c(3, 5, 1, 10, 12, 6) and I want to set all elements of this vector that are less than 6 to be equal to zero. What R code achieves this?

 
 
 
 

8. Which of the following statements about RStudio’s integrated development environment are correct?

 
 
 
 

9. Which of the following examples is the proper syntax for a function in R?

 
 
 
 

10. Suppose I have a vector x <- 1:4 and y <- 2:3. What is produced by the expression x + y?

 
 
 
 

11. In R language the following are all atomic data types EXCEPT

 
 
 
 

12. _________ is a function in R to get the number of observations in a data frame

 
 
 
 

13. A key property of vectors in R language is that

 
 
 
 

14. What function is used to test the missing observation in a data frame

 
 
 
 

15. Suppose I have a list defined as x <- list(2, “a”, “b”, TRUE). What does x[[2]] give me?

 
 
 
 

16. What is the class of the object defined by the expression x <- c(4, “a”, TRUE)?

 
 
 
 

17. The definition of free software consists of four freedoms (freedoms 0 through 3). Which of the following is NOT one of the freedoms that are part of the definition?

 
 
 
 

18. If I execute the expression x <- 4 in R language, what is the class of the object “x” as determined by the “class()” function?

 
 
 
 

19. The R language is a dialect of which of the following programming languages?

 
 
 
 
 

20. What should you use to assign a value to a variable in R?

 
 
 
 

rfaqs.com MCQs R Programming Language

MCQs R Programming Language 1

  • The R language is a dialect of which of the following programming languages?
  • The definition of free software consists of four freedoms (freedoms 0 through 3). Which of the following is NOT one of the freedoms that are part of the definition?
  • In R language the following are all atomic data types EXCEPT
  • If I execute the expression x <- 4 in R language, what is the class of the object “x” as determined by the “class()” function?
  • What is the class of the object defined by the expression x <- c(4, “a”, TRUE)?
  • If I have two vectors x <- c(1,3, 5) and y <- c(3, 2, 10), what is produced by the expression rbind(x, y)?
  • A key property of vectors in R language is that
  • Suppose I have a list defined as x <- list(2, “a”, “b”, TRUE). What does x[[2]] give me?
  • Suppose I have a vector x <- c(3, 5, 1, 10, 12, 6) and I want to set all elements of this vector that are less than 6 to be equal to zero. What R code achieves this?
  • ____________ is a function in R to get the number of observations in a data frame
  • What function is used to test the missing observation in a data frame
  • Which of the following statements about RStudio’s integrated development environment are correct?
  • Suppose I have a vector x <- 1:4 and y <- 2:3. What is produced by the expression x + y?
  • Which of the following statements about RStudio’s integrated development environment are correct?
  • A data analyst writes the code summary(penguins) to display a summary of the penguins dataset. Where in RStudio can the analyst execute the code?
  • What should you use to assign a value to a variable in R?
  • Which of the following examples is the proper syntax for a function in R?
  • What is the benefit of using the R programming language for data analysis?
  • Which of the following examples can you use in R for date/time data?
  • A data analyst inputs the following calculation in their R programming: $$basket_1 * 20 + basket_2 * 15 $$ Which arithmetic operators are the analyst using?
Learn R Language and FAQS

MCQs General Knowledge

MCQs in Statistics

Exploring Data in R: A Comprehensive R Tutorial

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Examination of data (Exploring Data), particularly graphical examination and representation of data is an important prelude to statistical data analysis and modeling. Note that there are some limitations on the kinds of graphs that we can create.

One should be familiar with standard procedures for exploratory data analysis, statistical graphics, and data transformation. We can categorize the graphical representation of data based on the variable’s nature (or type), the number of variables, and the objectivity of the analysis. For example, if we are comparing groups then comparison graphs such as bar graphs can be used. If we are interested in the kind of relationship between variables then a scatter plot can be useful.

  • Distributional Displays:
    The distributional displays include stem and leaf displays, histograms, density estimates, quantile comparison plots, and box plots.
  • Plots of the Relationship between two variables:
    The graphical representations of the relationship between two variables include various versions of scatter plots, scatter plot smoothers, bivariate density estimates, and parallel box plots.
  • Multivariate Displays:
    Multivariate graphical representations include scatter plot matrices, coplots, and dynamic three-dimensional scatter plots.

For exploring the data in R, the following are some examples:

Stem and Leaf Display and Histogram in R

attach(mtcars)
hist(mpg)
hist(mpg, nclass = 3, col = 3)
stem(mpg)
Histogram: Exploring Data in R

Exploring Data in R: Density Estimates

Consider the following R code for a representation of distribution by smoothing the histogram.

hist(mpg, probability = T, ylab = 'Density')
lines(density(mpg, lwd = 2))
points(mpg, rep(0, length(mpg)), pch = "|")
lines(density(mpg, adjust = 0.9), lwd = 1)

The hist() function constructs the histogram with probability=TRUE specifying density scaling. The lines() function draws the density estimate on the graph having a thickness of the line as double due to the parameter lwd=2. The points() function draws a one-dimensional scatter plot at the bottom of the graph by using a vertical bar as the plotting symbol. The second call to density in lines() the function with adjust=0.9, specifies a bandwidth of 0.9 the default value.

Quantile Comparison Plots

Quantile plots help in comparing the distribution of a variable with a theoretical distribution such as the normal distribution.

library(car)
qqPlot(mpg)

Note that the qqPlot() function is available in the car library. The qq.plot() function is defunct.

Exploring Data: Relationship Graphs

To explore the relationship between two quantitative variables use plot() function and for a more enhanced version of a scatter plot between two variables use scatterplot() function. This function plots the variables with least squares and non-parametric regression lines. For example,

plot(mpg, wt)
scatterplot(mpg, wt)
scatterplot(mpg, wt, labels = rownames(cyl))

CLICK to learn about plot() function in R

FAQs about R Language

  1. What do you mean by exploring data?
  2. What are the objectives of exploratory data analysis?
  3. What are the important visualizations for exploratory data analysis?
  4. For exploratory analysis, which graph is used for comparison purposes?
  5. For exploratory analysis, which graph is used to explore the relationship between variables?
  6. What is a quantile comparison plot?
  7. What is the objective of density estimation graphs?
  8. Name some of the multivariate plots used for EDA.

R Programming Language

Computer MCQs Online Test

Best R Language MCQs 1

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The post is about “MCQs R Language” which will help you to check your ability to execute some basic operations on objects in the R language and will help in understanding some basic concepts. This quiz may also improve your computational understanding, and it will also help you to learn and practice R language MCQs.

Please go to Best R Language MCQs 1 to view the test

R Language MCQs with Answers

R FAQS Logo: R Language MCQs
  • R is an interpreted language.  It can be accessed through ———–?
  • Who developed R?
  • Many quantitative analysts use R as their ———– tool.
  • R is an ———– programming language?
  • R was named partly after the first names of ———– R authors.
  • Packages are useful in collecting sets into a ———– unit
  • How many types of R objects are present in the R data type?
  • Which of the following is a primary tool for debugging?
  • Which function is used to create the vector with more than one element?
  • In R Language every operation has a ———– call.
  • The ———– in R is a vector.
  • Vectors come in two parts ———– and ———–.
  • ———– and ———– are types of matrices functions?
  • Which of the following commands will find the maximum value in the vector x, excluding the missing values
  • ———– initiates an infinite loop right from the start.
  • ———– command is used to skip an iteration of a loop.
  • In 1991, R was created by Ross Ihaka and Robert Gentleman in the Department of Statistics at the University of
  • R is technically much closer to the Scheme language than it is to the original ———– language.
  • R Language functionality is divided into a number of ———–.
R Language MCQs

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