In the previous section, we saw that the number `10` was identified as a `"double"` even though it is an integer. Let's delve into this peculiarity.

R can categorize numeric values into several types, which are:
- `numeric`/`double` - representing real numbers.
- `integer` - for integer numbers.
- `complex` - for numbers with both a real and an imaginary part.

Yet, in our previous exercise, `10` was classified as a `"double"`. To have R recognize it as an integer, appending `L` to the number is a straightforward method. For instance:

typeof(10) # Example of double type
typeof(10L) # Example of integer type

Differentiating between `10` and `10L` is important because of how memory is utilized — integers take up less space.

In the initial section, you’ll dive into the foundational elements of R, such as generating output and performing elementary operations. This section will conclude with an exploration of the theory behind variables.

You’ll become familiar with the vector class in R, which also handles individual values. Here, you’ll delve into the primary data types for singular values and learn how to manage multiple values of the same type simultaneously.

Factors, also known as categorical variables, are prevalent in the real world. Examples include blood types, currencies, nationalities, and brands. Unlike numerical variables, factors have a limited set of possible values.

R Introduction: Part I

Numbers

Task