When we talk about algorithms, it's really cool to see how they work in everyday life! Let’s break down a few examples of how long different types of algorithms take to run:

1. Constant Time - $O(1)$:

   • Example: Getting an item from an array. It doesn’t matter how big the array is, it always takes the same amount of time to get to an item, like finding the first one.

2. Linear Time - $O(n)$:

   • Example: Looking for a name in a list. If you have 100 names, you might have to check each one until you find the right one. Here, the more names you have, the longer it takes.

3. Quadratic Time - $O(n^2)$:

   • Example: Checking all combinations of items in a list, like finding duplicates. If you have 10 items, you will have to make 45 comparisons, and that number can grow quickly!

By understanding these examples, we can see how algorithms work differently based on time and space.