I like to use the metaphor of driving somewhere, and trying to estimate when you're going to get there. Maybe you have a hotel reservation, and you want to make sure you don't get there too early nor too late. Then (with some times filled in for example):

  +---------------------------------------+-------------------------------+--------------------------------+----------------------------------------+
  |                   .                   | Best Case (little/no traffic) | Average Case (average traffic) | Worst Case (car accident, snow-in etc) |
  +---------------------------------------+-------------------------------+--------------------------------+----------------------------------------+
  | Max time, upper bound (Big O)         | 30 minutes                    | 45 minutes                     | 1 hour 20 minutes                      |
  | Both min and max, tight bound (Theta) | 25 minutes                    | 35 minutes                     | 1 hour                                 |
  | Minimum time, lower bound (Omega)     | 15 minutes                    | 25 minutes                     | 50 minutes                             |
  +---------------------------------------+-------------------------------+--------------------------------+----------------------------------------+

So then you can start asking questions like - if I assume I'm in the average case, and I can show up earliest at 20 minutes from now, and show up latest at 50 minutes from now, can I guarantee that I will make it within that window? The answer in this case is yes, because our range is 25-45 minutes, so the earliest I can show up is in 25 minutes and the latest in 45 minutes.

This also helps explain why Big O is generally more useful - we can almost always be early to something, but we can almost never be late to something. So showing up 5 minutes early usually is not a problem.

It also shows why Theta is better than both - in this case, if we had this table we could completely ignore both the Big O row and Omega row, because Theta is a better bound for both min and max time.

Of course, in algorithmic complexity we replace the times with functions in terms of some variables, usually just n.