👉 Contamination math is a statistical technique used to estimate the proportion of contaminated items in a dataset when the true contamination rate is unknown and cannot be directly observed. It involves comparing the observed counts of contaminated items against a model that assumes contamination is random and independent, typically using a binomial distribution. The core idea is to calculate the probability that the observed number of contaminated items could occur by chance if contamination were truly random. This is often done using the binomial likelihood function, which is then normalized by the probability of observing those counts under the assumption of random contamination. The resulting estimate, known as the "contamination rate," is a point estimate that reflects the likelihood of contamination based on the data, with confidence intervals providing a measure of uncertainty around this estimate. This method is particularly useful in scenarios like quality control, epidemiology, and survey research where contamination rates are suspected but not directly measurable.
