Comparing sorting algorithms -- Insertion Sort vs. Merge Sort

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Insertion sort is faster for sorting fewer than 43 items, but the discussion highlights that sorting one item is a no-op and often overlooked. The exception of a single item should have been mentioned for clarity. The critical point of change between insertion sort and merge sort occurs around 40 to 41 items. Calculations show that for n = 40, insertion sort is slightly faster, but merge sort takes over as n increases. Understanding these nuances is essential for selecting the appropriate sorting algorithm based on the dataset size.
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Homework Statement
Suppose we are comparing implementations of insertion sort and merge sort on the same machine. For inputs of size n, insertion sort runs in 8n^2 steps, while merge sort runs in [itex]54n \log_2n [/itex] steps. For which values of n does insertion sort beat merge sort?
Relevant Equations
2^(n/8) < n
The answer says insertion sort runs faster when we're sorting less than 43 items. I agree but with the condition that the first item will not be faster. Why does the answer not mention this? Is it because it is insignificantly faster?
 
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It is because sorting a list of 1 item is a no-op and is usually not interesting.
Still, it should have mentioned that exception.
 
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Comparing 8 n^2 versus 54 n ceiling(log2(n)) the change occurs between n = 40 and n = 41.
ceiling log2(n) = 6, for n from 33 to 64 inclusive.
8 · (40^2) = 12800 versus 54 · 40 · 6 = 12960
8 · (41^2) = 13448 versus 54 · 41 · 6 = 13284
 
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