I was watching this lecture from MIT on dynamic programming, at the 22nd minute, the lecturer said that the formula for calculating the time complexity for a recursive dynamic programming solution using memoization is equal to the number of subproblems * the time of each subproblem without the recursive work.

I am having trouble understanding why this formula is true.

I understand the time complexity of a bottom-up solution because the loops make it obvious, but this top-down using memoization I find a bit confusing.

So if anyone cane share an intuitive way of understanding this formula it would be great.

Thank you in advance.