Answer each part TRUE or FALSE

$$\begin{gathered} \mathbf{a}.\mathbf{n}=\mathbf{o}\left(\mathbf{2}\mathbf{n}\right). \\ \mathbf{b}. \mathbf{2}\mathbf{n}=\mathbf{o}\left({\mathbf{n}}^2\right).\mathbf{A} \\ \mathbf{c}\mathbf{.}\mathbf{2}{}^{\mathbf{n}}\mathbf{=}\mathbf{o}\left(3^n\right)\mathbf{.}\mathbf{A} \\ \mathbf{d}\mathbf{.}\mathbf{1}\mathbf{=}\mathbf{o}\left(n\right)\mathbf{.} \\ \mathbf{e}\mathbf{.}\mathbf{n}\mathbf{=}\mathbf{o}\left(\log n\right)\mathbf{.} \\ \mathbf{f}\mathbf{.}\mathbf{1}\mathbf{=}\mathbf{o}\left(1/n\right)\mathbf{.} \end{gathered}$$

Here, it shows each part calculation which show correct theory and formula base answer in linear time,quadratic time etc.

$2n$seems to be linear time, therefore n represents linear time as well, therefore$n=O\left(2n\right)$

b) TRUE
$n^2$Since has been quadratic whereas $2n$seems to be linear,$2n=O\left(n^2\right)$

c) TRUE
$2^n$ involves time that is exponentially andbecomes exponentially larger than $2^n$thus .$2^n=O\left(3^n\right)$

d) TRUE
$1$ represents continuous time (i.e., a moment), and therefore it is undeniably$1=O\left(n\right)$ where n is linear times.

e) FALSE
$n$is linear time$\log n$ Because it would be the logarithmic time, that's less than linear, $ncouldbeinBigOoflogn$.

f) FALSE
Important Note: $1=o\left(\frac{1}{n}\right)$s rather tough to obtain; it just implies that the algorithm will run quicker for a greater number of inputs; more tasks, less time; less tasks, more time.