The following formula is the mathematical expression of Bayes' law. How does this formula apply to perceptual processes? (1 = image, Sx = stimulus) P(Sx| 1) - P(I | Sx) P(Sx) 1 pts It shows that the most likely image to be seen is the one that occurs the most often. It shows how our perceptions are entirely due to what we expect to see. It shows that our perception is probabilistic and is only influenced by inverse optics and not the expectations we have about the world. It shows that the perception resulting from an image can be predicted from the likelihood that the image was due to a particular stimulus and our prior belief that the stimulus would occur