We often have to compute functions of quantities that have statistical (or other) errors. Error propagation involves computing how the error of the function inputs translates to the error of the function outputs.

This is the first edition of some notes on techniques of error propagation. The notes cover what I find to be the most common technique of error propagation: linearization.