Calculating the RMS of a 4072x22x10 matrix can be challenging without using loops, especially when aiming for a result that reflects the RMS of each of the 10 matrices in the third dimension. The initial suggestion to calculate the RMS for a single slice of the matrix (A(:,:,1)) is insufficient, as the goal is to obtain a 4072x22 matrix representing the RMS values across all slices. A proposed method involves using the mean function to average across the third dimension, but it does not directly apply to the standard deviation, which complicates the process. To achieve the desired outcome, additional coding may be necessary to compute the standard deviation for each slice effectively. The discussion emphasizes the need for efficient computation methods in MATLAB to handle large matrices without running into memory issues.