Course Content

R Introduction: Part I

Arithmetic Operations with Vectors

Vectors in R offer a significant advantage due to their flexibility with various operations. For instance, if you have two vectors of the same length, you can easily perform addition or subtraction on an element-by-element basis.

Additionally, vectors can undergo arithmetic operations with single numbers, which apply the operation to each element of the vector. For example, let's create a vector with the numbers 10, 20, 30 and add 40, 25, 5 to each corresponding element:


              123456
            
# Vectors
a <- c(10, 20, 30)
b <- c(40, 25, 5)
# Addition
c <- a + b
c

Now, let's go ahead and multiply each element by 2:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
# Multiplication
d <- c * 2
d

R also provides a variety of aggregate and statistical functions. Let's explore two of the most common ones:

sum() - calculates and returns the sum of all vector elements;
mean() - computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
d <- c * 2
# Calculating the sum
sum(d)

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item	Price	Items sold
Sofa	$340	5
Armchair	$150	7
Dining table	$115	3
Dining chair	$45	15
Bookshelf	$160	8

Construct a vector called sold with the respective values from the Items sold column.
Calculate the revenue by multiplying the prices and sold vectors and then output the result.
Display the total sum of the revenue vector.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 10

Arithmetic Operations with Vectors


              123456
            
# Vectors
a <- c(10, 20, 30)
b <- c(40, 25, 5)
# Addition
c <- a + b
c

Now, let's go ahead and multiply each element by 2:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
# Multiplication
d <- c * 2
d

R also provides a variety of aggregate and statistical functions. Let's explore two of the most common ones:

sum() - calculates and returns the sum of all vector elements;
mean() - computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
d <- c * 2
# Calculating the sum
sum(d)

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item	Price	Items sold
Sofa	$340	5
Armchair	$150	7
Dining table	$115	3
Dining chair	$45	15
Bookshelf	$160	8

Construct a vector called sold with the respective values from the Items sold column.
Calculate the revenue by multiplying the prices and sold vectors and then output the result.
Display the total sum of the revenue vector.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 2. Chapter 10

Arithmetic Operations with Vectors


              123456
            
# Vectors
a <- c(10, 20, 30)
b <- c(40, 25, 5)
# Addition
c <- a + b
c

Now, let's go ahead and multiply each element by 2:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
# Multiplication
d <- c * 2
d

R also provides a variety of aggregate and statistical functions. Let's explore two of the most common ones:

sum() - calculates and returns the sum of all vector elements;
mean() - computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
d <- c * 2
# Calculating the sum
sum(d)

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item	Price	Items sold
Sofa	$340	5
Armchair	$150	7
Dining table	$115	3
Dining chair	$45	15
Bookshelf	$160	8

Construct a vector called sold with the respective values from the Items sold column.
Calculate the revenue by multiplying the prices and sold vectors and then output the result.
Display the total sum of the revenue vector.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!


              123456
            
# Vectors
a <- c(10, 20, 30)
b <- c(40, 25, 5)
# Addition
c <- a + b
c

Now, let's go ahead and multiply each element by 2:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
# Multiplication
d <- c * 2
d

R also provides a variety of aggregate and statistical functions. Let's explore two of the most common ones:

sum() - calculates and returns the sum of all vector elements;
mean() - computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:


              123456
            
a <- c(10, 20, 30)
b <- c(40, 25, 5)
c <- a + b
d <- c * 2
# Calculating the sum
sum(d)

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item	Price	Items sold
Sofa	$340	5
Armchair	$150	7
Dining table	$115	3
Dining chair	$45	15
Bookshelf	$160	8

Construct a vector called sold with the respective values from the Items sold column.
Calculate the revenue by multiplying the prices and sold vectors and then output the result.
Display the total sum of the revenue vector.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Section 2. Chapter 10

Switch to desktop for real-world practiceContinue from where you are using one of the options below