I have data tables with statistical data per year of various figures. There are some gaps in the data, so I need to approximate the gaps. A simple linear extrapolation won't do because I might have some data similar to the following examples:
5 7 10 12 15 25 N/A 25 28 31 N/A 9 15 10 0 N/A N/A 0
Or I might have multiple interdependent sets of data like meat production and meat spoilage:
Meat production: 2 3 3 4 5 5 7 9 15 25 62 110
Meat spoilage: 0 0 1 1 2 2 3 4 N/A N/A N/A N/A
I'm sorry if a question like this is common or has been answered many times, I'm very inexperienced in math. so much so that I don't even know what area of math deals with these kind of things.
There are various mathematical techniques for estimating missing values in a data series. They all fall under the general heading of interpolation.
If you have an idea about how one variable depends on another, and you want to asses the validity of this idea, then you need to know about regression analysis.
In either case you need to have some idea about how you expect your data to behave (for example, you have already rejected linear interpolation) to give you a starting point.