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:
It would be to figure out what cancers someone could exactly so no need for a biopsy
One surface is larger than the other surface
Answer:
=F5*$F$12+F5
Explanation:
If we want to increment the salaries in the cell F5, we must multiply the cell F5 by cell F12, and then we must sum that result.
If we want to drag the formula from the cell F5 to F10, we must use the dollar symbol $ to apply the same percent in our formula.
For example:
F12 = 5% = 0.05
F5 = 10,000
=F5*$F$12+F5
=10,000×0.05+10,000 = 10,500
B. Television. It provided <span>instant communication and information to a massive audience for the first time in 1927.
Hope this helps :)</span>
