Podcast
Questions and Answers
What does the round() function do when applied to a vector?
What does the round() function do when applied to a vector?
In R, scalars are treated as single-element vectors.
In R, scalars are treated as single-element vectors.
True
What is the result of applying the function round() to the number 1.2?
What is the result of applying the function round() to the number 1.2?
1
The function f(x, c) returns the value of (x + c) ________.
The function f(x, c) returns the value of (x + c) ________.
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Match the R function with its description:
Match the R function with its description:
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What happens when you try to call the function f() with a vector as the second argument?
What happens when you try to call the function f() with a vector as the second argument?
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The + operator in R is treated as a function.
The + operator in R is treated as a function.
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What is the expected output of the function f(1:3, 1)?
What is the expected output of the function f(1:3, 1)?
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What is the main purpose of the subset() function in R?
What is the main purpose of the subset() function in R?
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The which() function in R returns the values that satisfy a given condition.
The which() function in R returns the values that satisfy a given condition.
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What does the filtering expression x[x > 5]
return if x
contains NA values?
What does the filtering expression x[x > 5]
return if x
contains NA values?
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The function used to identify the positions within a vector where a condition holds is called _____ function.
The function used to identify the positions within a vector where a condition holds is called _____ function.
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Match the R operation with its output:
Match the R operation with its output:
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What does the code first1 <- x[ifelse(x > 6, 2*x, 3*x)]
evaluate?
What does the code first1 <- x[ifelse(x > 6, 2*x, 3*x)]
evaluate?
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The result of the expression z * z > 8
is a vector of Boolean values.
The result of the expression z * z > 8
is a vector of Boolean values.
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What is the advantage of using ifelse() over traditional if-then-else constructs in R?
What is the advantage of using ifelse() over traditional if-then-else constructs in R?
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What does the expression x[j,]
return?
What does the expression x[j,]
return?
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The operation of filtering rows using a Boolean vector is not vectorized.
The operation of filtering rows using a Boolean vector is not vectorized.
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What operator is used for calculating the logical AND of two Boolean vectors in R?
What operator is used for calculating the logical AND of two Boolean vectors in R?
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The command z <- x[z %% 2 == 1,]
extracts rows of x where the elements of z are ___ numbers.
The command z <- x[z %% 2 == 1,]
extracts rows of x where the elements of z are ___ numbers.
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What does the function drop
do when applied in data operations?
What does the function drop
do when applied in data operations?
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Using &&
will yield the same result as using &
for logical operations on vector elements.
Using &&
will yield the same result as using &
for logical operations on vector elements.
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If we apply the expression m[m[,1] > 1 & m[,2] > 5,]
, what type of rows are extracted from m?
If we apply the expression m[m[,1] > 1 & m[,2] > 5,]
, what type of rows are extracted from m?
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Match the following commands with their functionalities:
Match the following commands with their functionalities:
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What function is used to add columns to a matrix in R?
What function is used to add columns to a matrix in R?
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The rbind() function can be used to add rows to an existing matrix.
The rbind() function can be used to add rows to an existing matrix.
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What happens to the original matrix when you reassign a new matrix to it?
What happens to the original matrix when you reassign a new matrix to it?
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Using the cbind()
function allows you to bind a column of ______ to the existing matrix.
Using the cbind()
function allows you to bind a column of ______ to the existing matrix.
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When creating a matrix in a loop, it is more efficient to:
When creating a matrix in a loop, it is more efficient to:
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Match the function to its description:
Match the function to its description:
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What is the time penalty mentioned when repeatedly creating a matrix?
What is the time penalty mentioned when repeatedly creating a matrix?
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In R, using the function ______()
allows for the recycling of values when creating a new matrix.
In R, using the function ______()
allows for the recycling of values when creating a new matrix.
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What type of data structure is suggested for storing employee information?
What type of data structure is suggested for storing employee information?
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The numerical indices of list components must always be used when accessing data in a list.
The numerical indices of list components must always be used when accessing data in a list.
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What Boolean value indicates that an employee is a member of a union?
What Boolean value indicates that an employee is a member of a union?
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To access a specific component of a list by name, you can use the syntax j$______
.
To access a specific component of a list by name, you can use the syntax j$______
.
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Which of the following methods can be used to access the salary component of a list named j?
Which of the following methods can be used to access the salary component of a list named j?
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Match the following methods of accessing list components with their descriptions:
Match the following methods of accessing list components with their descriptions:
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Using single brackets to access a list component returns an element in the original data type.
Using single brackets to access a list component returns an element in the original data type.
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What is the advantage of using names instead of numerical indices in lists?
What is the advantage of using names instead of numerical indices in lists?
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What type of vector is the result of using unlist() on the list containing the values "Joe", "55000", and "TRUE"?
What type of vector is the result of using unlist() on the list containing the values "Joe", "55000", and "TRUE"?
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The unlist() function will always return a numeric vector if the original list contains numeric values.
The unlist() function will always return a numeric vector if the original list contains numeric values.
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What function is used to concatenate lists in R, which also includes an option for recursive flattening?
What function is used to concatenate lists in R, which also includes an option for recursive flattening?
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In R, when using the function unlist(), the components of the list are coerced to a common mode, typically resulting in a ____________ vector.
In R, when using the function unlist(), the components of the list are coerced to a common mode, typically resulting in a ____________ vector.
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Match the following terms with their descriptions:
Match the following terms with their descriptions:
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What is the result of calling the c() function with the recursive argument set to TRUE on a list where the components themselves are lists?
What is the result of calling the c() function with the recursive argument set to TRUE on a list where the components themselves are lists?
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When combining lists, the default value for the recursive argument in the c() function is TRUE.
When combining lists, the default value for the recursive argument in the c() function is TRUE.
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What type does R choose when mixing numeric and character types in a list during unlist()?
What type does R choose when mixing numeric and character types in a list during unlist()?
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Study Notes
Syllabus
- R Programming is a course for III B.Sc CSDA students.
- The course is for Semester V.
- Syllabus includes 5 units covering R programming, data structures, operations, data frames, modeling, and classes & objects.
Unit I
- Introducing R: Introduction to R, R data structures, functions in R, vectors, scalars, declarations, recycling, vectorized operations, NA and NULL values, filtering, and vector element names.
- Features of R Programming: Open-source, strong graphical capabilities, highly active community, a wide selection of packages, comprehensive environment, complex statistical calculations, distributed computing, running code without a compiler, interfacing with databases, data variety, machine learning, and data wrangling. Cross-platform support and compatibility with other programming languages are also noted.
Unit II
- Matrices and Operations: Creating matrices, matrix operations, applying functions to matrix rows and columns, adding and deleting rows/columns, vector/matrix distinction, avoiding dimension reduction, higher dimensional arrays, lists, creating lists, general list operations, accessing list components, values, applying functions to lists, and recursive lists.
Unit III
- Data Frames: Creating data frames, matrix- operations in frames, merging data frames, applying functions to data frames, factors, tables, factors and levels, common functions used with factors, working with tables, other factors and table-related functions, control statements, arithmetic and Boolean operators, default values for arguments, returning Boolean values, Functions are objects, environment and scope issues, writing upstairs, recursion, replacement functions, tools for composing function code, math and simulation in R.
Unit IV
- Classes and Objects: S3 and S4 classes, managing objects, input/output, accessing keyboard and monitor, reading and writing files, accessing the internet, string manipulation, graphics, creating graphs, customizing graphs, saving graphs, and creating three-dimensional plots.
Unit V
- Interfacing R to other languages, Parallel R, basic statistics, linear model, generalized linear models, non-linear models, time series, and autocorrelation, clustering.
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Description
Test your knowledge of fundamental R programming concepts, including functions like round(), operator usage, and vector handling. This quiz covers various aspects of R syntax and functionality, providing a comprehensive overview for beginners.