Ordered factors
Since "Male"
and "Female"
are unordered (or nominal) factor levels, R returns a warning message, telling you that the greater than operator is not meaningful. As seen before, R attaches an equal value to the levels for such factors.
But this is not always the case! Sometimes you will also deal with factors that do have a natural ordering between its categories. If this is the case, we have to make sure that we pass this information to R…
Let us say that you are leading a research team of five data analysts and that you want to evaluate their performance. To do this, you track their speed, evaluate each analyst as "slow"
, "medium"
or "fast"
, and save the results in speed_vector
.
This exercise is part of the course
Introduction to R
Exercise instructions
As a first step, assign speed_vector
a vector with 5 entries, one for each analyst. Each entry should be either "slow"
, "medium"
, or "fast"
. Use the list below:
- Analyst 1 is medium,
- Analyst 2 is slow,
- Analyst 3 is slow,
- Analyst 4 is medium and
- Analyst 5 is fast.
No need to specify these are factors yet.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Create speed_vector
speed_vector <-