Chamber-based measurement of greenhouse gas emissions from soil is a common technique.  However, when changes in chamber headspace gas concentrations are small over time, determination of the flux can be problematic.  Several factors contribute to the reliability of measured fluxes, including: sampling/analytical precision, chamber deployment time, number of time point samples collected over the course of the chamber deployment, and the methodology used to compute the flux.  This study used Monte Carlo simulation to investigate all of these factors on the Type I error rate of chamber flux measurements.  The sampling/analytical precisions (coefficients of variation) investigated ranged from 0.01 to 0.12.  Three chamber deployment times (0.5 h, 0.75 h, and 1.0 h) and two sampling intensities (3 time points or 4 time points) were tested.  The flux calculation methods used were: i) linear regression, ii) a quadratic method whereby a 2^nd degree polynomial was fit to the data and the first derivative was evaluated at time zero, and iii) a method developed by Hutchinson and Mosier that accounts for chamber impacts on gas diffusion.  The quantitative relationships between these variables and Type I error rate, enabled the determination of the minimum detection limits of measured soil gas fluxes.