We present a method to minimize, or even cancel out, the nuisance parameters affecting a measurement. Our approach is general and can be applied to any experiment or observation. We compare it with the bayesian technique used to deal with nuisance parameters: marginalization, and show how the method compares and improves by avoiding biases. We illustrate the method with several examples taken from the astrophysics and cosmology world: baryonic acoustic oscillations, cosmic clocks, Supernova Type Ia luminosity distance, neutrino oscillations and dark matter detection. By applying the method we recover some known results but also find some interesting new ones. For baryonic acoustic oscillation (BAO) experiments we show how to combine radial and angular BAO measurements in order to completely eliminate the dependence on the sound horizon at radiation drag. In the case of exploiting SN1a as standard candles we show how the uncertainty in the luminosity distance by a second parameter modeled as a metallicity dependence can be eliminated or greatly reduced. When using cosmic clocks to measure the expansion rate of the universe, we demonstrate how a particular combination of observables nearly removes the metallicity dependence of the galaxy on determining differential ages, thus removing the age-metallicity degeneracy in stellar populations. We hope that these findings will be useful in future surveys to obtain robust constraints on the dark energy equation of state.