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.
The answer is B bc obliteration is related to covering the document
Answer:
Answered below
Explanation:
//Program is written in Python programming //language.
number_of_trees = int(input ("Enter number of trees purchased: "))
height_of_trees = float(input("Enter height of trees: "))
delivery_status = input("Do you want trees delivered? enter yes or no ")
price_of_two_meters = 20
total_price = number_of_trees * price_of_two_meters
//Invoice
print (number_of_trees)
print(height_of_trees)
print (total_price)
print (delivery_status)
I believe the answer is B<span />
In the year 2028 I don't believe our digital video viewing experience would change too much considering most, if not all, the population is already satisfied with how easy, simple, and versatile our current experience is. If everything changes one thing will for sure remain unchanged. That one thing is cinemas, I don't think cinemas will ever change much as they provide a constant source of revenue while providing a place for family and friends to get together to watch a movie before it becomes available to other sources.
