2.6. Determining confidence intervals for the parameters. Another important objective of mathematical modeling is to calibrate the selected model, i.e. the model selected from the previously described process (see Section 2.4 above) by determining confidence intervals for its parameters. We consider a model H with a given set of freely varying parameters that defines a vector (h); i.e. each component of h is a parameter of the model. Within each population, the model predicts a distribution for the number of infected cats (male or female). Each possible model outcome (defined as a vector of 30 integers representing the number of infected males and females within each of the 15 populations) has a probability of occurrence. What we want to determine is the values h of the free parameters for which the observed data is a plausible outcome of the model. We accept that the data is a plausible outcome of the model when its likelihood is within the range of likelihood values of typical model outcomes, as described below.