Prior parameter variance
Hi, I am trying to understand the Prior Parameter Variance option for the Bayesian D-optimal design. JMP help says: "The value that you enter is the square root of the reciprocal of the prior variance. A larger value represents a smaller variance and therefore more prior information that the effect is not active." I am a bit confused, since I thought that if I enter larger value, that would info...