Computer Science Canada Big O Notation :| |

Author: | mathews411 [ Sat Jul 05, 2014 11:57 am ] |

Post subject: | Big O Notation :| |

So I'm taking a summer computer science class this year, and the topic of Big O notation has surfaced. In class it seemed fairly basic, we looked at simple equations (Ex. 8log n + 7n), the answer would be O(n) as it is the term that grows the fastest. That's stuff i can do. Now we were given an assignment of similar type questions, but they threw something in that caused me to doubt what I know. Usually, when we would encounter a log, it would simple just be log(n), now they included log(n^2), or any kind of number for the exponent. For example I'll give a similar question that was in my assignment so if anyone can answer it they not doing my assignment for me. 3log(n^9) + 2nlog(n >2). Me and a friend both assumed the answer is O(nlogn), as nlogn grows faster then log(n). But then we started to talk about if it might be O(n^k) from the n^9 . In class, we never talked about how if a term is in a logarithm if it grows the fastest, or if it defaults to the original log and becomes a slower growth function. Any help will be greatly appreciated, as Big O notation makes me die a little on the inside. Hope I dint make this post to confusing! |

Author: | Dreadnought [ Sat Jul 05, 2014 12:57 pm ] |
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Post subject: | Re: Big O Notation :| |
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Remember that you have
With that in mind you should be able to compare the behavior of log(n^k) with n*log(n). |

Author: | rdrake [ Sat Jul 05, 2014 1:08 pm ] |

Post subject: | Re: Big O Notation :| |

If you expand out out, you get . Recall from the logarithmic rules that where , so we get: So Or you can be a jerk and say it's which it technically is. |

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