Course Content

# R Introduction: Part I

1. Basic Syntax and Operations

R Introduction: Part I

## Intervals

To categorize numerical data into groups, you can use the `cut()`

function in R, which assigns each number to a category based on specified intervals. For instance, if you have a continuous variable like height, you can categorize individuals as 'tall', 'medium', or 'short' based on height ranges.

The `cut()`

function in R allows you to divide numerical data into categorical factors. Here's how you can use it:

Among the parameters listed, these are crucial for categorizing data:

`x`

is the numerical vector to be categorized.`breaks`

can be an integer specifying the number of intervals, or a vector of cut points.`labels`

provide names for the categories.`right`

indicates if the intervals should be closed on the right.`ordered_result`

determines if the resulting factors should have an order.

To create three categories, set `breaks`

to `3`

or provide a vector with four cut points to form three intervals, for instance (a,b], (b,c], (c,d].

For our example of categorizing height:
We choose `c(0, 160, 190, 250)`

for `breaks`

to divide the data into three groups: (0, 160], (160, 190], and (190, 250]. We also set `ordered_result`

to `TRUE`

to define a logical order among categories (e.g., small < medium < tall).

# Task

- Given a vector of numerical grades, here's how to categorize them as factor levels:
- [0;60) - F
- [60;75) - D
- [75;85) - C
- [85;95) - B
- [95;100) - A

- Create a variable
`grades_f`

that stores the factor levels with the specified breaks and labels, considering the ordering, and use`right = FALSE`

to include the left boundary of the intervals.`breaks`

-`c(0, 60, 75, 85, 95, 100)`

`labels`

-`c('F', 'D', 'C', 'B', 'A')`

`ordered_result`

-`T`

(*to order the factor values*)`right`

-`F`

(*to include the left boundary of an interval, not right*)

- Output the contents of
`grades_f`

.

Everything was clear?