Let's briefly summarize what we learned in this part of the course.

R allows us to create vectors, which are data structures representing sequences of elements of the same data type. They can store **numbers** (numerical vectors), **text values** (character vectors), or **logical** `TRUE`

/`FALSE`

values (logical vectors).

We define vectors with either the

`c()`

function or the

**colon** (

`:`

) operator.

c(1,2,3,4,5)
1:5

**Addition**, **subtraction**, **multiplication**, and **division** operations are all defined for vectors and occur in a **memberwise fashion**. They can occur between two vectors or between a vector and a numerical value.

You can access the elements of a vector using the **bracket** `[]`

operator. You can access the "i"th element using

a[i]

You can also retrieve several elements at once by **listing the index positions**:

ages[c(3,5,7)]
ages[1:5]

A third way to access vector elements is to use conditional operators inside the brackets:

ages[ages > 40]

There are many functions that we can use to analyze numerical data, such as `min()`

, `max()`

, `mean()`

, `median()`

, and `quantile()`

. Alternatively, we can use the `summary()`

function to display all this information at once:

summary(ages)

Finally, you can use all functions on vector subsets:

summary(ages[ages >= 18])