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NikAS [45]
3 years ago
15

Someone claims that the big O notation does not make sense at all, and they give the following example. An algorithm A that proc

esses an input set of N elements takes time, in seconds, given by T(N) = 10000*N + 0.00001*N^3. They say that the large constant (10000) associated with the N will always dominate over the small constant (0.00001) associated with the N^3. You say that this algorithm A is:_____
Computers and Technology
1 answer:
Svetllana [295]3 years ago
7 0

Answer:

Big Oh notation is used to asymptotically bound the growth of running time above and below the constant factor.

Big Oh notation is used to describe time complexity, execution time of an algorithm.

Big Oh describes the worst case to describe time complexity.

For the equation; T(N) = 10000*N + 0.00001*N^3.

To calculate first of all discard all th constants.

And therefore; worst case is the O(N^3).

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Answer:

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Explanation:

Define the <em>constants</em>

Ask user to enter the <em>gross income</em> and <em>number of dependents</em>

Calculate the <em>income</em> using formula (income = gross_income - STANDART_DEDUCTION - (DEPENDENT_DEDUCTION * number_of_dependents))

Calculate the <em>tax</em>

Print the <em>tax</em>

<em />

round(number, number of digits) -> This is the general usage of the <em>round</em> function in Python.

Since we need <u>two digits of precision</u>, we need to modify the program as str(<u>round(incomeTax, 2</u>)).

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