// Big O Questions

// 1.
//   1) constant O(1)
//   2) linear O(n)

// 2.
//   constant because the size of the in put doesn't change the time complexity.

// 3. ************
//   O(a * b)
//   because the function has 2 inputs that can be of varying value.

// 4.
//   O(n)
//   because the for loop had to operate on every item in the array.

// 5.
//   O(n)
//   because the if statement is constant it gets dropped for the for loop.

// 6.
//   O(n^2)
//   because nested for loops operating on the same input.

// 7.
//  O(n)
//  because the array operations are all push,
//  they get dropped and the linear time complexity of the for loop is left.

// 8.
//   O(logN)
//   because it splits the array in half with every loop.

// 9.
//   O(1)
//   constant time. because array item look up is constant.

// 10.
//   O(n)
//   worst case the for loop would have to loop N times.

// 11.

//13
  // 1) O(n)
  //because larger num of sheep the more operations.

  // 2) O(n)
  //because larger input means funciton calls itself more.