#Create two vectors with random, normal distribution numbers: one with even, and another with odd number of elements.
bunch_of_nums_even <- rnorm(100)
bunch_of_nums_odd <-  rnorm(101)
#Sort one of the vectors according to number size
sorted_nums <- sort(bunch_of_nums_even) #< I used even for this example - switch to odd to test that as well. 
num_length <- length(sorted_nums)
#If the length of the sorted vector is divisble by 2...
if ((num_length %% 2) == 0) {
  print("Vector is even")
  #... create a vector of the 2 middle elements...
  num_medians <- c((num_length/2),((num_length/2)+1))
  #... and calculate their average; that is the mean.
  num_median <- mean(sorted_nums[num_medians])
  #                  ^ This is a vector of the 2 middle spots in our even vector
} else #< If the length of the sorted vector is odd...
{
  print("Vector is odd")
  #Get the index of the median number by substracting 1 from the total count, divide by half and add one again.
  num_median_index <- (((num_length + 1)/2)) #<There's probably a better way to do this.
  #The median is the number in the index we figured out earlier; pull it from the sorted vector.
  num_median <- sorted_nums[num_median_index]
}
cat("Median is:", num_median)