Answer:
I would rather use:
(b) 10,000 batches of 10 observations each.
Step-by-step explanation:
It is easier to have 10,000 batches of 10 observations each than to have 50 batches of 2,000 observations. Human errors are reduced with fewer observations. For example, Hadoop, a framework used for storing and processing big data, relies on batch processing. Using batch processing that divides the 100,000 stationary waiting times into 10 observations with 10,000 batches each is more efficient than having 2,000 observations with 50 batches each.
