R Language Basic Questions

The post is about some R Language Basic Questions. The questions are related to the use of R Language, some preliminaries in R, the Use of Rstudio, R Commander, some functions in R, etc.

R Language Basic Questions

What is Rstudio and how to use it?

The Rstudio is software used as an editor for writing R and other Language-related programming codes. To use Rstudio, follow the steps:

Step 1: Download and Install Rstudio
Step 2: Open Rstudio
Sep 3: Click on the menu: File -> New -> R Script
Step 4: Paste the R code (write it) in the new source code area. Running the R program on the command line or elsewhere will start the console. One can paste the R code in the R Console or editor area.
Step 5: Click the “Source” button above the code area.

One can also use the console in Rstudio. If a user clicks “Run” instead of “Source” user input might not work properly. One can use the R documentation.

What are Preliminaries in R?

The following are some preliminaries in R Language:

  • R is a case-sensitive language
  • # is the comment tag
  • R is installed with the default library (also called packages). One can add/import extra packages to the library using the command library().
  • To use a library function one must load it first into the memory using the command load().
  • Variable names in R language cannot start with “.” (dot), “+” (plus sign), or “=” (minus sign).

Explain What is R

R is a data analysis software that is used by analysts, quants, statisticians, data scientists, and others. R Language is a leading tool for statistics, machine learning, and data analysis. It allows for the easy creation of objects, functions, and packages.

List out some of the functions that the R Language Provides

The following is a short list of functions that R provides:

  • mean()
  • median()
  • var()
  • lm()
  • summary()
  • print()
  • glm()
  • plot()

Explain How One Can Start the R Commander GUI

To start the R Commander, type the command, library(Rcmdr) into the R console. Note that one must first install the Rcmdr package.

install.packages("Rcmdr")
# Start the R Commander GUI
library(Rcmdr)

What is R Software for Statistics and Data Analysis

R is an open-source programming language. It is a software environment for statistical computing and graphics techniques. The R language is widely used by statisticians and data miners for developing statistical software/packages and performing data analysis.

What is Mean in R?

The mean is the average of the numbers: a calculated “central” value of a set of numbers. To calculate the mean of a data set, add up all the numbers, then divide by how many numbers there are. In R, one can do this by using the command:

x = c(1, 2, 4, 7, 8, 9, 4, 8)
mean(x)
R Language Basic Questions, R FAQs

What is the Median in R?

The Median is the “middle” of a sorted list of numbers. For an even amount of numbers, things are slightly different. In the case of an even number of observations, one can find the middle pair of numbers, and then find the average of these two middlemost numbers. The median can be computed in R by using the command:

x = c(1, 2, 4, 7, 8, 9, 4, 8)
median(x)

Note that R itself decides about a number of observations either there are even or odd number of observations.

Statistics for Data Analysts

R and Database Management System Quiz 20

The post is about R and Database Management System Quiz with Answers. There are 20 multiple-choice questions about R language and database connectivity with R. Let us start with the R and Database Management System Quiz now.

Online MCQs about R and Database management system Quiz with Answers

1. Which RODBC function is best suited for retrieving information about the structure and attributes of database tables?

 
 
 
 

2. Which of the following concepts illustrates a data frame in R language?

 
 
 
 

3. Which of the following is one of the two components of ODBC?

 
 
 
 

4. Which of the following statements correctly describes the ODBC Driver Manager?

 
 
 
 

5. Which of the following is the simplest way to update individual observations in a data frame?

 
 
 
 

6. When designing a relational database, which aspect is primarily addressed by normalization techniques?

 
 
 
 

7. Which function in the RJDBC package is used to close the database connection after accessing the data?

 
 
 
 

8. What is the best way to provide a data analyst with knowledge of a database schema or structure, often depicted using an entity-relationship (ER) diagram?

 
 
 
 

9. When mapping data types between R and a database, which of the following should you consider converting to strings?

 
 
 
 

10. In the context of mapping data between R and relational databases, how does logical data from R typically represent when exchanged with a database server?

 
 
 
 

11. A variable in R language is comparable to which of the following relational database concepts?

 
 
 
 

12. Which of the following statements about database packages for R are true?

 
 
 
 

13. How can a relational database help R handle memory issues?

 
 
 
 

14. Which R function saves a single data structure to a .Rda file?

 
 
 
 

15. Which of the following is the first step that you must take before using the RJDBC package for R language? https:/rfaqs.com

 
 
 
 

16. What is the first step you must complete outside of R before installing the RODBC package?

 
 
 
 

17. What does RJDBC stand for?

 
 
 
 

18. What benefit does using a relational database with R provides even when the data does not reside in the database?

 
 
 
 

19. What are the two categories of relational database access packages in R language? https://rfaqs.com

 
 
 
 

20. Choose a statement that best describes declarative referential integrity.

 
 
 
 

R and Database Management System Quiz with Answers

R and Database Management System Quiz

  • How can a relational database help R handle memory issues?
  • Which R function saves a single data structure to a .Rda file?
  • Which of the following concepts illustrates a data frame in R language?
  • When mapping data types between R and a database, which of the following should you consider converting to strings?
  • When designing a relational database, which aspect is primarily addressed by normalization techniques?
  • Which of the following is the simplest way to update individual observations in a data frame?
  • A variable in R language is comparable to which of the following relational database concepts?
  • In the context of mapping data between R and relational databases, how does logical data from R typically represent when exchanged with a database server?
  • What benefit does using a relational database with R provides even when the data does not reside in the database?
  • Choose a statement that best describes declarative referential integrity.
  • Which function in the RJDBC package is used to close the database connection after accessing the data?
  • What does RJDBC stand for?
  • Which of the following statements about database packages for R are true?
  • Which of the following statements correctly describes the ODBC Driver Manager?
  • What are the two categories of relational database access packages in R language? https://rfaqs.com
  • Which of the following is the first step that you must take before using the RJDBC package for R language? https:/rfaqs.com
  • Which of the following is one of the two components of ODBC?
  • What is the best way to provide a data analyst with knowledge of a database schema or structure, often depicted using an entity-relationship (ER) diagram?
  • Which RODBC function is best suited for retrieving information about the structure and attributes of database tables?
  • What is the first step you must complete outside of R before installing the RODBC package?

Sociology Quiz with Answers

Statistical Simulation

Matrices in R Programming

The post is about matrices in the R Programming Language. These questions are about basic concepts and will improve the understanding of R programming-related job interviews or educational examinations.

Question 1: Write the general format of Matrices in R Programming Language.

Answer: The general format of matrices in R Programming Language is

Mymatrix <- matrix (vector, nrow = r , ncol = c , byrow = FALSE,
                    dimnames = list (char_vector_for_rowname, char_vector_for_colnames)
                   )
matrices in r programming language

Question 2: Explain what is transpose.

Answer: The transpose is used to re-shape data. Before performing any analysis, R language provides various methods such as the transpose method for reshaping a dataset. To transpose a matrix or a data frame t() function is used.

Question 3: What is the main difference between an Array and a Matrix?

Answer: A matrix in R language is always a two-dimensional rectangular data set as it has rows and columns. However, an array can be of any number of dimensions, while each dimension of an array is a matrix. For example, a $3\times3\times2$ array represents 2 matrices each of dimension $3\times3$.

Question 4: What are R matrices and R matrices functions?

As discussed earlier, a matrix is a two-dimensional rectangular data set. The matrices in R Programming language can be created using vector input to the matrix() function. Also, a matrix is a collection of numbers or elements that are arranged into a fixed number of rows and columns. Usually, the numbers or elements of the matrix are the real numbers, therefore, the data elements must be of the same basic type. Two types of matrix functions can be used to perform different computations on matrices in R Programming:

  • apply()
  • apply()

Question 5: How many methods are available to use the matrices?

Answer: There are many methods to solve the matrices like adding, subtraction, negative, etc.

Question 6: What is the difference between matrix and data frames?

    Answer: A data frame can contain different types of data but a matrix can contain only similar types of data.

    Question 7: What is apply() function in R?

    Answer: The apply() function in R returns a vector (or array or list of values) obtained by applying a function to the margins of an array or matrix. the general syntax of the apply() function in R language is:

    apply(X, MARGIN, FUN, …)

    A short description of the arguments for the apply() functions are

    • X is an array, including a matrix.
    • MARGIN is a vector giving the subscripts to which the function will be applied.
    • FUN is the function to be applied.
    • … is optional arguments to FUN

    Question 8: What is the apply() family in R?

    Answer: The apply() functions in the R language are a family of functions in the base R. The family of these functions allows the users to act on many chunks of data. An apply() function is a loop, but runs faster than loops and often must less code. There are many different apply functions.

    • There is some aggregating function. They include mean, or the sum (includes return a number or scalar);
    • Other transforming or subsetting functions.
    • There are some vectorized functions. They return more complex structures like lists, vectors, matrices, and arrays.
    • One can perform operations with very few lines of code in apply().

    Question 9: What is sapply() in R?

    Answer: A Dimension Preserving Variant of “sapply” and “lapply”. The sapply is a user-friendly version. It is a wrapper of lapply. By default sapply returns a vector, matrix, or array. The general syntax of sapply() and lapply() is

    Sapply(X, FUN, ..., simplify = TRUE, USE.NAMES = TRUE)
    Lapply(X, FUN, ...)

    A short description related to arguments of the above functions are:

    • X is a vector or list to call sapply.
    • FUN is a function.
    • … is optional arguments to FUN.
    • simplify is a logical value that defines whether a result is been simplified to a vector or matrix if possible.
    • USE.NAMES is logical; if TRUE and if X is a character, use X as the name for the result unless it had names already.
    Rfaqs.com matrices in R Programming Language

    Statistics and Data Analysis