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Big O notation and Worst case Analysis of an Algorithm?
in this we will ans the following question Is bigO notation a tool to do best, worst, & average case analysis of an algorithm? Big O for worstcase running time and Ω is for the bestcase, but why is Ω used in worst case sometimes? What is the difference between Big O notation and Worst case Analysis of an Algorithm? As for my understanding both will give upper bound of any given function. Please explain the difference. There is a common misconception that BigO means worstcase, BigOmega means bestcase, BigTheta means averagecase. How do O and Ω relate to worst and best case?
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algorithm
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asymptoticcomplexity
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What is the best way for a beginner to learn programming?
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programming
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datastructuresandalgorithms
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