The posterior is now interpreted as a probability distribution in the parameters and it therefore describes our belief or confidence in the parameters after the data has been observed/measured. On the other hand stands the prior p(θ) which contains any prior information about the parameters. For us, p(θ) for example includes that reactivity ratios must be greater than zero.