Gather empirical timing data by running your implementations for various values of $n.$ Use

a C$++$ or Python timing program. You will need enough data points to establish the shape

of the best$-$fit curve $($at least $6$ data points or more$),$ and you should use $n$ sizes that are

large enough to produce large time values $($multiple seconds or even minutes$)$ to minimize

instrumental error.

Draw a scatter plot and fit line for your timing data. You could use a spreadsheet program

$($e$.$g$.$ Excel, Google Sheets, Numbers, OpenOffice$).$ The instance size $n$ should be on the

horizontal axis and elapsed time should be on the vertical axis. Your plot should have a

title; and each axis should have a label and units of measure.

Conclude whether or not your empirically$-$observed time efficiency data is consistent, or

inconsistent, with the big$-$O efficiency classes predicted above.