I am learning about Big O Notation running times and amortized times. I understand the notion of O(n) linear time, meaning that the size of the input affects the g
First I recommend you to read following book;
Algorithms (4th Edition)
Here is some functions and their expected complexities. Numbers are indicating statement execution frequencies.
Following Big-O Complexity Chart also taken from bigocheatsheet
Lastly very simple showcase there is shows how it is calculated;
Anatomy of a program’s statement execution frequencies.
Analyzing the running time of a program (example).