title: Big O notation -- does more complex mean faster or slower
body: <p>I'm learning about big O notation and I'm kind of confused. I don't think I really get how "complexity" effects an algorithm, and I can't tell if I'm looking at things backwards.</p>
  
  <p>is the order of complexity from least to most complex: O(1), O(log n), O(n), O(n log n), O(n^2)? or do I have it backwards?</p>
  
  <p>If this is the correct order, I would guess that a program with a complexity of O(n^2) would process large sets of data faster than a program with O(n log n). However after testing a bubble sort(O(n^2)) and a quick sort (O(n log n)), it's obvious that the O(n^2) sort processed WAY slower than O(n log n). So I'm confused.... is complexity good or bad? Will an algorithm be fast(in terms of how long it takes to complete the program) if it's more complex, or will a complex program will be slower?</p>