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To understand and interpret the observed Spectral Energy Distributions (SEDs)of starbursts, theoretical or semi-empirical SED models are necessary. Yet,while they are well-founded in theory, independent verification and calibrationof these models, including the exploration of possible degeneracies betweentheir parameters, are rarely made. As a consequence, a robust fitting methodthat leads to unique and reproducible results has been lacking. Here weintroduce a novel approach based on Bayesian analysis to fit the Spitzer-IRSspectra of starbursts using the SED models proposed by Groves et al. (2008). Wedemonstrate its capabilities and verify the agreement between the derived bestfit parameters and actual physical conditions by modelling the nearby,well-studied, giant HII region 30 Dor in the LMC. The derived physicalparameters, such as cluster mass, cluster age, ISM pressure and coveringfraction of photodissociation regions, are representative of the 30 Dor region.The inclusion of the emission lines in the modelling is crucial to breakdegeneracies. We investigate the limitations and uncertainties by modellingsub-regions, which are dominated by single components, within 30 Dor. Aremarkable result for 30 Doradus in particular is a considerable contributionto its mid-infrared spectrum from hot ({\simeq} 300K) dust. The demonstratedsuccess of our approach will allow us to derive the physical conditions in moredistant, spatially unresolved starbursts.

The Physical Conditions in Starbursts Derived from Bayesian Fitting of Mid-IR SEDS: 30 Doradus as a Template