Again, suppose we have a vector name containing names of 50 students. grade is another numeric vector containing final marks of those students.

We run the following code:

dat

Question

Again, suppose we have a vector name containing names of 50 students. grade is another numeric vector containing final marks of those students.

We run the following code:

dat <- tibble(name, grade)
dat$grade[2] <- as.character(dat$grade[2])
is.numeric(dat$grade)

The output should be

BlackTom AI · Accepted Answer

We start with a vector named name containing 50 student names and a numeric vector grade with their final marks. The code creates a tibble dat combining name and grade.

Next, the line dat$grade[2] <- as.character(dat$grade[2]) attempts to replace the second element of the grade column with its character representation. In R, if you assign a character value into a numeric vector, the entire vector is coerced to character to accommodate mixed types. Since dat$grade is the numeric column of the tibble, this assignment will convert the whole grade column to character type, not just the second element.

Then we call is.numeric(dat$grade). The is.numeric function returns TRUE only if the object is of type numeric (or integer). After the previous coercion, dat$grade is a character vector (each element is a character string representing a number), so is.numeric(dat$grade) yields FALSE for every element.

Therefore, the result of is.numeric(dat$grade) is a logical vector of length 50, where every entry is FALSE. In R text form, that is FALSE FALSE FALSE ... FALSE (a logical vector of length 50, all FALSE).

Key points for understanding this outcome:
- Assigning a character to a numeric vector coerces the whole vector to character.
- is.numeric returns FALSE for any character vector, even if the elements look like numbers.
- The final output is a logical vector with 50 FALSE values corresponding to each element of the original grade vector.

COMM_V 205 101 102 103 2025W1 In-class Exercise (ICE) 15

Again, suppose we have a vector name containing names of 50 students. grade is another numeric vector containing final marks of those students. We run the following code: dat <- tibble(name, grade) dat$grade[2] <- as.character(dat$grade[2]) is.numeric(dat$grade) The output should be

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