I am preparing a paper in the field of Computer Science.
In order to report test results, we usually run a number of tests and report the average of those tests.
For each test, we generate random data.
Because of the randomness, at some points, the results may come out not as expected.
For instance, a graph may be like:
Usually, one should explain why on points 8, 11 and 12 there is a decrease on the plot. Probably, it is because of that randomness.
Not hand-crafting all the graph, but just manipulating a few points makes the graph acceptable:
Since three weeks or so, I work my ass off and try to figure out why my resulting graph looks like the first one. Sometimes I feel like yielding to temptation and just modify the raw data before I go crazy.
I believe, at this point the title became misleading, so let me make it clear:
I am not seeking an advice on data manipulation. I will not manipulate my data. However, I ask to myself "how the hell this can be detected?"
And now, I don't only ask to myself, but to whole community. How is this detected? For editors, referees out there, have you ever detected something like this?