How is Bayesian Inference Implemented in Catalysis Research?
Implementation of Bayesian inference in catalysis research typically involves several steps:
Define the Hypothesis and Prior: Start by defining the hypothesis or model and establishing the prior distribution, which represents the initial belief about the parameters before observing the data. Collect Data: Gather experimental data relevant to the catalytic process under investigation. Apply Bayes' Theorem: Use Bayes' Theorem to update the prior distribution with the new data, resulting in the posterior distribution. Analyze the Posterior: Analyze the posterior distribution to make inferences about the parameters and predict future outcomes.
