I have the following 3 data sets for the same quantity with errors as shown in the figure in different colors. How to find the best fit function of 1) each data set separately 2) combined of the 3 data set. Suppose I find the best fit function of each data set separately; then how to combine the three best-fit functions correctly so that I can have a single fit function. Which method will give the more accurate results; finding one single fit function for all the data sets or finding separately each and then adding them up? How I would check the accuracy.
ListPlot[{{Around[0.2, 0.1], Around[1, 0.1], Around[2, 0.2],
Around[3, 0.3]}, {Around[0.5, 0.1], Around[2.5, 0.1],
Around[3.5, 0.2], Around[3.5, 0.3]}, {Around[0.8, 0.1],
Around[1.5, 0.1], Around[2.8, 0.2], Around[1.8, 0.3],
Around[5, 0.5]}}, Frame -> True]
LinearModelFit
orNonlinearModelFit
. However, your questions touch upon basic fitting concepts, rather than their implementation in Mathematica. I recommend that you ask in the statistics forum first. $\endgroup$