title: Big O for worst-case running time and Ω is for the best-case, but why is Ω used in worst case sometimes?
body: <p>I'm confused, I thought that you use Big O for worst-case running time and Ω is for the best-case? Can someone please explain? </p>
  
  <p>And isn't (lg n) the best-case? and (nlg n) is the worst case?  Or am I misunderstanding something? </p>
  
  <blockquote>
    <p>Show that the worst-case running time of Max-Heapify on a heap of size
    n is Ω(lg n). ( Hint: For a heap with n nodes, give node values that
    cause Max-Heapify to be called recursively at every node on a path
    from the root down to a leaf.)</p>
  </blockquote>
  
  <p>Edit: no this is not homework. im practicing and this has an answer key buy im confused. 
  <a href="http://www-scf.usc.edu/~csci303/cs303hw4solutions.pdf" rel="noreferrer">http://www-scf.usc.edu/~csci303/cs303hw4solutions.pdf</a> Problem 4(6.2 - 6)</p>
  
  <p>Edit 2: So I misunderstood the question not about Big O and Ω? </p>