Match each everyday task to the growth rate of its work as $n$ grows.

• Finding a page number in a book’s index → $O(\log n)$
• Reading every page of a book once → $O(n)$
• Comparing every page with every other page → $O(n^{2})$
• Opening the book’s front cover → $O(1)$

Big-O is the "what happens when n doubles" question: $O(1)$ shrugs, $O(\log n)$ adds one step, $O(n)$ doubles, $O(n^{2})$ quadruples. Growth class, not raw speed, decides what is feasible at scale.