Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
Answer:
The best answer would be
Explanation:
To access this command ...
Select the Format tab - Properties - Paragraph properties - Bleeds and spaces
Answer:
Programming is a set of instructions i.e. Input given by the user to the computer to perform a particular task and give the desired result i.e. output.
Final Answer
s=0
for i in range(1,26):
s=s+ i
print(s)
Explanation:
IF THE ANSWER IS CORRECT THEN MARK A BRAINLEST
