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How long an algorithm takes to run depends on many factors including implementation details and hardware.\\xa0 However, the formal analysis of algorithms focuses on how they will perform in the worst case as the input size grows.\\xa0 We refer to an algorithm\'s runtime as it\'s "O" which is a function of its input size "n".\\xa0 For example, O(n) represents a linear algorithm - one that takes roughly twice as long to run if you double the input size.\\xa0 In this episode, we discuss a few everyday examples of algorithmic analysis including sorting, search a shuffled deck of cards, and verifying if a grocery list was successfully completed.

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