Big$-$O: The characterization of an algorithm using a T$($n$)$ relation for some input size n$.$

Select the statements that apply to Big$-$O$.$

Group of answer choices

Quantifies an algorithm based on the number of operations, or steps taken.

If the problem size increases, certain terms dominate.

O$($n$^4)$ is better than O$($n$^2).$

The order of magnitude function describes the part of T$($n$)$ that increases the fastest as n increases.

O$(1)$ describes an algorithm that will always execute in the same time $($or space$)$ regardless of the size of the input data set.