I know that these "averages" questions have been asked a lot already, however I still a not sure which would be better in my situation.
I have a device that needs calibration, and gathers data over some time. In the end, the data used for calibration will be the interpolation of all the gathered data. To do so, I simply wanted to make an average of all the data: However I'm not sure which strategy would be more adapted to the situation:
Doing an average of all the gathered data at the end
Or: Making an average of the last data and the next one, and then keep the result as the last data.
The second method would obviously save some space, but in terms of outcome, I'm honestly not too sure where the difference lies.
Let's say I have a car driving the same race a hundred times. What trajectory would I get by using the first method, what trajectory would I get by using the second one? This has nothing to do with my problem, but I think I might understand better which method to use if I knew the answer to this. Let's clarify this example first, though. Imagine the trajectory of my car was plotted by an array of (x;y) coordinates. After having let my car run 4 times, I will thus obtain 4 different sets of coordinates. I now want to interpolate these coordinates to make the best possible estimate on an average set of coordinates representing the trajectory the car would take if the deviation from its path would be 0. What result would both of the methods above produce? (Namely: 1. For each coordinate in all of the sets, create a new coordinate that is (x-average; y-average) 2. For the first two coordinates, create a coordinate A((x0+x1)/2;(y0+y1)/2), then a coordinate B((xA+x2)/2;(yA+y2)/2), etc.