Determing Big Oh Of Given Data I'm trying to determine the big O time complexity of the following
data set where the first column is the input size, and the second column is the execution time in seconds. Where possible, I should determine the exponent of the dominant term and provide an estimate for the coefficient on the dominant term.

I made the following
graph of the data and a log/log graph to try and figure it out. At first I thought it might have been 1/n or something along those lines but as n gets quite large, the execution time increases again instead of asymptotically approaching a value.
The log graph having such a distinct pattern leads me to believe that the answer will lie there but I'm stuck as to where to go from here. Any help would be great.
You can't.  You can't infer big-O complexity from a finite set of data points, as big-O complexity is about asymptotics.  See, e.g., How to fool the plot inspection heuristic?.