Important Quiz R Programming Debug 6

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The article is about “Quiz R Programming” which covers different aspects of debugging a function’s execution. Let us start with the Quiz R Programming Debug.

MCQs about Debugging and Traceback in R Language

1. Which function is better for analyzing fast-running functions: profvis( ) or microbenchmark( )?

 
 
 
 

2. You are working with a large data frame. It contains so many columns that they don’t all fit on the screen simultaneously. You want a quick list of all the column names to understand better what is in their data. What function should they use?

 
 
 
 

3. Where in RStudio can you find the export menu for saving plots?

 
 
 
 

4. Which of the following functions initiates an interactive debugging environment that allows you to step through code one expression at a time?

 
 
 
 

5. Which of the following files in R have names that follow widely accepted naming convention rules?

 
 
 
 

6. In R, what includes reusable functions and documentation about how to use the functions?

 
 
 
 

7. You are compiling an analysis of the average monthly costs for your company. What summary statistic function should you use to calculate the average?

 
 
 
 

8. What does calling trace(“f”) for function “f( )” do

 
 
 
 

9. What does the Rprof( ) function do?

 
 
 
 

10. What is the microbenchmark package useful for?

 
 
 
 

11. Which of the following functions allows you to temporarily insert pieces of code into other functions to modify their behavior?

 
 
 
 

12. When should the traceback( ) function be called?

 
 
 
 

13. A data analyst wants a high-level summary of the structure of their data frame, including the column names, the number of rows and variables, and the type of data within a given column. What function should they use?

 
 
 
 

14. What is the name of the popular package archive dedicated to supporting R users’ authentic, validated code?

 
 
 
 

15. What does the traceback( ) function do?

 
 
 
 

16. You want to create functions, documentation, sample data sets, and code tests they can share and reuse in other projects. What should you create to help them accomplish this?

 

 
 
 
 

17. You want to store a vector in a variable. What type of operator would you use to do this?

 

 
 
 
 

18. Debugging is the process of

 
 
 
 

19. What does the profvis( ) function do?

 
 
 
 

20. You want to create a vector with the values 21, 12, 39, in that exact order. After specifying the variable, what R code chunk lets you create the vector?

 
 
 
 

Debugging is an essential skill in programming, including R programming. In R Programming Language, the debug() function in R allows the user to step through the function’s execution, line by line. At any point, we can print out values of variables or produce a graph of the results within the function.

MCQs Quiz R Programming Debug

Quiz R Programming with Answers

  • Debugging is the process of
  • Which of the following functions initiates an interactive debugging environment that allows you to step through code one expression at a time?
  • Which of the following functions allows you to temporarily insert pieces of code into other functions to modify their behavior?
  • What does the traceback() function do?
  • When should the traceback() function be called?
  • What does calling trace(“f”) for function “f( )” do
  • What is the microbenchmark package useful for?
  • What does the Rprof( ) function do?
  • What does the profvis( ) function do?
  • Which function is better for analyzing fast-running functions: profvis( ) or microbenchmark( )?
  • In R, what includes reusable functions and documentation about how to use the functions?
  • What is the name of the popular package archive dedicated to supporting R users’ authentic, validated code?
  • You want to create a vector with the values 21, 12, 39, in that exact order. After specifying the variable, what R code chunk lets you create the vector?
  • You are compiling an analysis of the average monthly costs for your company. What summary statistic function should you use to calculate the average?
  • You are working with a large data frame. It contains so many columns that they don’t all fit on the screen simultaneously. You want a quick list of all the column names to understand better what is in their data. What function should they use?
  • Where in RStudio can you find the export menu for saving plots?
  • Which of the following files in R have names that follow widely accepted naming convention rules?
  • You want to store a vector in a variable. What type of operator would you use to do this?  
  • You want to create functions, documentation, sample data sets, and code tests they can share and reuse in other projects. What should you create to help them accomplish this?  
  • A data analyst wants a high-level summary of the structure of their data frame, including the column names, the number of rows and variables, and the type of data within a given column. What function should they use?

Statistics and Data Analysis

Online Quiz Website with Answers

Backward Deletion Method Step by Step in R

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Introduction to Backward Deletion Method

With many predictor variables, one can create the most statistically significant model from the data. There are two main choices: forward stepwise regression and backward deletion method.
In Forward Stepwise Regression: Start with the single best variable and add more variables to build your model into a more complex form.

In Backward Deletion (Backward Selection) Regression: put all the variables in the model and reduce the model by removing variables until you are left with only significant terms.

Backward Deletion method (Step by Step Procedure)

Let’s start with a big model and trim it until you get the best (most statistically significant) regression model. This drop1() command can examine a linear model and determine the effect of removing each one from the existing model. Complete the following steps to perform a backward deletion. Note that the model has different R packages for the Backward and Forward Selection of predictors.

Step 1: (Full Model)

Step 1: To start, create a “full” model (all variables at once in the model). It would be tedious to enter all the variables in the model, one can use the shortcut, the dot notation.

mod <- lm(mpg ~., data = mtcars)

Step 2: Formula Function

Step 2: Let’s use the formula() function to see the response and predictor variables used in Step 1.

formula(mod)
Backward Deletion Method

Step 3: Drop1 Function

Step 3: Let’s use the drop1() function to see which term (predictor) should be deleted from the model

drop1(mod)

Step 4: Remove the Term

Step 4: Look to remove the term with the lowest AIC value. Re-form the model without the variable that is non-significant or has the lowest AIC value. The simplest way to do this is to copy the model formula in the clipboard, paste it into a new command, and edit out the term you do not want

mod1 <- lm(mpg ~ ., data = mtcars)

Step 5: Examine the Effect

Step 5: Examine the effect of dropping another term by running the drop1() command once more:

drop1(mod1)

If you see any variable having the lowest AIC value, if found, remove the variable and carry out this process repeatedly until you have a model that you are happy with.

FAQS about Backward Deletion Method in R

  1. Write a step-by-step procedure to perform the Backward Deletion Method in r.
  2. How one can examine the effect of dropping the term from the model?
  3. What is the use of the formula function term in lm() model?
  4. What is the use of drop1() function in r?

Learn more about lm() function

Online MCQs Quiz Website

Important MCQs R Vectors Data Structure 5

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This quiz “MCQs R Vectors” covers the topics related to creating different types of vectors in R, vector operations, Functions for vectors, naming, and concatenating vectors in R. Let us start with the Quiz on MCQs R Vectors.

Please go to Important MCQs R Vectors Data Structure 5 to view the test

In R Langauge, a vector data type is a fundamental data structure that represents a sequence of elements having the same data type. R Vectors can be of various types, including numeric, character, logical, and more.

MCQs R Vectors Data Structure

MCQs R Vectors

  • The following command can be used to print an object “x” in R.
  • What is the output of the following R code? r <- 0:10 r[2]
  • ________ operator is used to create integer sequences.
  • What is the output of the following R code? y <- 0:5 vector(y) y[3]
  • How can one define ‘infinity’ in R Language? How can one define ‘undefined value’ in R Language?
  • What is the output of the following R code? x <- c(“a”, “b”) as.numeric(x)
  • Identify the wrong statement:
  • If a command is incomplete at the end of a line, R will give a different prompt, by default it is _____
  • Which of the described R Language best
  • Which function can you use to create a different plot for each type of cut of diamond?
  • A data analyst inputs the following code in RStudio: sales_1 <- 100 * sales_2. Which of the following types of operators does the analyst use in the code?
  • What are ggplot2, tidyr, dplyr, and forcats all a part of?
  • Which tidyverse package is used for data visualization?
  • An analyst is organizing a dataset in RStudio using the following code: arrange(filter(Storage_1, inventory >= 40), count)
  • Which of the following examples is a nested function in the code?
  • Which tidyverse package contains a set of functions, such as select(), that help with data manipulation?
  • Which of the following statements about vectors in R is correct?
  • A data analyst finds the code mdy(10211020) in an R script. What is the year of the date that is created?
  • A data analyst wants to combine values using mathematical operations. What type of operator would they use to do this?
  • A data analyst wants to store a sequence of data elements with the same data type in a single variable. What R concept allows them to do this?

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