Data Structures and Algorithms The Complete Masterclass - Big O(n^2) Complexity

The video tutorial explains quadratic time complexity, often represented as O(N^2), which occurs when using nested loops. It provides an example with a list of seven elements, demonstrating how each element is paired with every other element, resulting in 49 operations. The tutorial also covers calculating big O notation, simplifying it to N^2 by removing constants. Additionally, it discusses complexity when dealing with different input sizes, using N and M to represent the number of inputs for two lists. The video concludes with a brief mention of the next lecture topic.

How does the big O notation apply to the function discussed in the lecture?

What changes would affect the complexity of the function discussed, and how?