Measurements of chemical experiment outcomes may differ even when the experiment is repeated under the same conditions. This means that the recorded measurements will spread around some mean value or the true response. It is common to represent noisy measurements as having a normal distribution with a certain mean and a standard deviation, where the mean represents the true response. The more replicated experiments and their response measurements there are, the better one can capture the true distribution of the response and the spread of the noisy measurements around the true response. This is often modelled as additive Gaussian noise ε ∼ N (0, σ 2 ), where σ is the standard deviation.