Thanks for the suggestions. Hopefully the course will be fully released by next month and there will be extra resources not found in the original book. Let me try to clarify some of the things you asked about and maybe it will make it into the next version.
It sounds like you were wondering how to calculate the number of guesses required in the worst case for simple search and binary search if you have 4,000,000,000 items. With simple search, the number of guesses is simply equal to the number of items. That's pretty easy. 4 million items is 4 million guesses. Binary search is a little trickier. With binary search, after every guess, you divide the number in half. You keep doing that until the number left is one.
It's simpler to explain using 16 items instead of four million, but the concept is the same.
16 / 2 = 8 (first guess)
8 / 2 = 4 (second guess)
4 / 2 = 2 (third guess)
2 / 2 = 1 (fourth guess)
So with 16 items, you need 4 guesses for binary search and 16 guesses for simple search. Understanding logarithms can make this easier (since log 2 of 16 equals 4) but it is not required to understand the concept. That is why I did not go into more detail about logarithms in the course.
For the traveling salesperson problem, you ask why 5 routes have 120 permutations and 6 routes have 720 permutations. It is because five factorial is 120 and six factorial is 720. Factorial means multiplying an integer with all the integers below it. Here's is an example:
Five factorial (written like "5!") means 1 * 2 * 3 * 4 * 5 = 120
Six factorial (written like "6!") means 1 * 2 * 3 * 4 * 5 * 6 = 720
Let me know if you have any more questions!
