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: 8
And if you hold shift while typing it, it gives *
Answer:
C. analyzes data and trends and predicts future data and trends.
Explanation:
Predictive analytics can be defined as a statistical approach which typically involves the use of past and present data ( factual informations) in order to determine unknown events or future performances of a business firm or organization. It is focused on determining what is likely to happen in the future.
For example, a data analyst trying to determine how to effectively stock his company's warehouses incase of an anticipated pandemic and he's using current sales data to project the demands.
Hence, a predictive data analyst is an individual who analyzes data and trends and predicts future data and trends.
