## 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 applies 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.

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

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.

# 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.

Everything was clear?

Course Content

# R Introduction: Part I

R Introduction: Part I

## 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 applies 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.

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

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.

# 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.

Everything was clear?